153 Quantization Jobs - Page 3

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 8.00 + years Salary : USD 4074-4814 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 5 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - A leading US-based digital consultancy with a track record of excellence) What do you need for this opportunity? Must have skills required: FastAPI, Hugging Face, Knowledge graphs, MLOps, Quantization, TensorFlow, AI, ChatGPT, LLM Fine-tuning, Rag (retrieval-augmented generation), Vector databases, Python A leading US-based digital consultancy with a track record of excellence is Looking for: Role : Senior Python / AI Engineer: Hybrid (Mumbai) Experience : 6+years Work Location : Mumbai : Hybrid (One week in a month) Engagement : Contract To Hire (Initially 5 months to start) : Start date : Immediate Timing : 2pm to 11 pm IST Interview process: 2 Rounds(Aptitude round + Technical round ) Job Description : Overall Job Mission: To design, develop, implement, and optimize AI-driven solutions by effectively leveraging and integrating existing Large Language Models and related technologies. Outcomes (What does the person need to achieve?) LLM Integration & Application Development: Successfully integrate existing LLMs (e.g., GPT, LLaMA, Mistral, Claude, Gemini) into Python-based applications to deliver AI-powered features. (e.g., Develop and deploy 3 applications with LLM-driven functionality within the first 6 months with a user satisfaction rating of 4.5/5). Prompt Engineering & Optimization: Design, implement, and rigorously test prompts to maximize the effectiveness and accuracy of existing LLMs for specific application requirements. (e.g., Improve the accuracy of LLM-driven features by 20% through prompt engineering best practices). AI Solution Optimization: Optimize the performance, efficiency, and scalability of AI solutions built with LLMs, focusing on factors like response time, cost-effectiveness, and resource utilization. (e.g., Reduce the average response time of LLM-based applications by 15% while maintaining accuracy). Data Handling & Retrieval: Implement effective data processing, including preprocessing and cleaning of text datasets, and utilize vector databases to enable efficient information retrieval for LLM applications. (e.g., Achieve a 90% success rate in retrieving relevant information from vector databases for LLM queries). Deployment & Scalability: Deploy and scale LLM-powered applications on cloud platforms to support a growing user base and ensure high availability. (e.g., Successfully scale LLM applications to handle a 50% increase in user traffic without performance degradation). Competencies (How does the person need to behave?) LLM Application Expertise: Possesses strong skills in integrating and applying existing LLMs through APIs and libraries, with a focus on prompt engineering and application development. Python Development & AI Frameworks: Demonstrates proficiency in Python programming and AI/ML frameworks (Hugging Face, PyTorch, TensorFlow) for building and deploying LLM-based solutions. Problem Solving & Adaptability: Exhibits the ability to solve challenges related to LLM integration, optimize performance, and adapt to the evolving landscape of LLM technologies. Collaboration & Communication: Effectively communicates technical solutions and collaborates with cross-functional teams to deliver impactful AI applications. Results Orientation: Focuses on delivering functional, efficient, and scalable AI solutions that meet business needs and user expectations. Required Skills & Experience- Must-Have Hands-on Experience: Python programming with AI/ML frameworks (Hugging Face, PyTorch, TensorFlow). Hands-on experience working with LLMs and fine-tuning. Experience in prompt engineering and optimizing AI model outputs. Building APIs with FastAPI or Flask for AI model integration. Familiarity with vector databases and embedding models. Experience with LangChain, LlamaIndex, or Retrieval-Augmented Generation (RAG). Nice to Have (or Learn on the Job): Knowledge of quantization techniques (LoRA, GPTQ, vLLM, ONNX) for efficient model deployment. Experience working with knowledge graphs and reasoning-based AI. Background in MLOps for tracking and managing AI models. How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

MaxIQ is building the industry’s first revenue AI platform that transforms how B2B SaaS companies manage customer journeys. Join us to pioneer autonomous agentic systems that empower sales teams with predictive insights and intelligent automation. Role Overvie wYou’ll architect AI agents that autonomously optimize revenue operations for sales, customer success, and RevOps teams .These agents will replace fragmented workflows with predictive guidance, real-time customer journey analysis, and context- aware automation. Your work will directly contribute to MaxIQ’s mission of turning customer interactions into predictable revenue engine s Key Responsibiliti esAutonomous Agent Developme nt: Build AI agents using LangChain, LlamaIndex, and Python/Java to automate deal qualification, churn prediction, provide valuable insights and calculate customer health scori ngSales Intelligence Augmentati on: Design agents that provide role-specific insights (e.g., deal guidance for AEs, renewal alerts for CSMs) while integrating with tools like Salesfor cePrompt Engineering & R AG: Evolve chat-based assistants into autonomous systems using retrieval-augmented generation and real-time data pipeline s.Observability Sta ck: Implement tracing, logging, and monitoring for agent decisions to ensure transparency in revenue-critical operatio nsScalable Inferen ce: Optimize LLM performance for high-throughput environments using quantization, model pruning, and cloud-native deployme nt Qualificati onsEducat ion: BS/MS in Computer Science, Data Science, or related fie lds Technical Sk i lls:5+ years with Gen AI frameworks, LLM fine-tuning, and agentic architect uresExpertise in Python/Java, AWS/GCP, and containerized microserv icesExperience building observability into AI agents is a plus Cultura l Fit:Passion for solving complex revenue operations challenges in B2B SaaSStartup mindset – thrives in fast-paced environments with high owne rship Why MaxIQ?Category-Defining P roduct: Shape the future of AI- powered customer journey mana gementAgentic AI Focus: Work on cutting-edge autonomous systems that process millions of customer interactions dailyGlobal Impact: Deploy solutions used by enterprises to drive reductions in sales cycle times and higher customer lifetime value Show more Show less

Overview: Seeking an engineer to build and optimize high-throughput, low-latency LLM inference infrastructure using open-source models (Qwen, LLaMA, Mixtral) on multi-GPU systems (A100/H100). You’ll own performance tuning, model hosting, routing logic, speculative decoding, and cost-efficiency tooling. Must-Have Skills: Deep experience with vLLM, tensor/pipe parallelism, KV cache management Strong grasp of CUDA-level inference bottlenecks, FlashAttention2, quantization Familiarity with FP8, INT4, speculative decoding (e.g., TwinPilots, PowerInfer) Proven ability to scale LLMs across multi-GPU nodes (TP, DDP, inference routing) Python (systems-level), containerized deployments (Docker, GCP/AWS), load testing (Locust) Bonus: Experience with any-to-any model routing (e.g., text2sql, speech2text) Exposure to LangGraph, Triton kernels, or custom inference engines Has tuned models for <$0.50/M token inference at scale Highlight: Very good rate card for the best candidate fit. Show more Show less

Transform 800,000 hectares of greenhouses into fully-autonomous unmanned food production sites At Eternal, we're building the future of sustainable food production. Our mission is to convert the world's existing greenhouses into unmanned facilities that can produce fresh food year-round - addressing the critical need to double food production by 2050 while facing severe labor shortages, water scarcity, and climate challenges. About the Role Join our world-class computer vision team as we revolutionize horticulture automation. Whether you're a recent graduate eager to make your mark or an experienced engineer looking for your next challenge, you'll develop cutting-edge perception systems that enable robots to understand and interact with complex greenhouse environments - from identifying ripe produce to detecting plant diseases and optimizing crop health. As a Computer Vision Engineer at Eternal, you'll be part of a high-performance culture that values first-principles thinking and rapid iteration. You'll work at the intersection of classical computer vision and modern deep learning, creating perception systems that operate reliably in challenging agricultural environments with varying lighting, occlusions, and organic variability. You'll collaborate with a distributed team across our Cologne HQ and Bengaluru office, pushing the boundaries of what's possible in agricultural computer vision while delivering practical solutions that work 24/7 in production environments. What You'll Do Design and implement robust computer vision algorithms for crop detection, ripeness assessment, and precise localization in dynamic greenhouse environments Develop deep learning models for multi-class segmentation, object detection, and tracking of plants, fruits, and agricultural structures Create real-time perception pipelines that process 2D/3D sensor data for robotic decision-making with sub-centimeter accuracy Build intelligent systems that adapt to varying environmental conditions, including changes in lighting, plant growth stages, and seasonal variations Optimize vision algorithms for edge deployment on robotic platforms, balancing accuracy with computational efficiency Implement continuous learning systems that improve model performance through data collected from our deployed robot fleet Collaborate cross-functionally with robotics engineers, AI/ML researchers, and crop scientists to deliver end-to-end perception solutions Qualifications Core Requirements (All Levels) Bachelor's degree in Computer Science, Electrical Engineering, Applied Mathematics, or related field (or graduating by Summer 2025) Strong programming skills in C++ and/or Python for computer vision applications Understanding of fundamental computer vision concepts: image processing, feature detection, camera calibration, and 3D geometry Experience with deep learning frameworks (PyTorch, TensorFlow) and classical CV libraries (OpenCV) Familiarity with Linux environments and version control systems Passion for solving complex real-world problems with tangible impact Experience Levels New Graduate / Entry Level (0-2 years) Recent graduate or final year student with strong academic performance Hands-on computer vision experience through internships, research projects, or competitions Demonstrated programming skills through coursework or personal projects Understanding of CNNs and basic deep learning architectures Early Career (2-5 years) Solid foundation in both classical and deep learning-based computer vision Experience deploying at least one vision system from research to production Proficiency with modern architectures (YOLO, Mask R-CNN, Vision Transformers) Understanding of model optimization techniques and edge deployment Senior Level (5-8 years) Proven track record of deploying vision systems in production environments Experience with 3D vision, multi-sensor fusion, or SLAM algorithms Knowledge of model optimization for embedded systems (quantization, pruning, distillation) Ability to mentor junior engineers and lead technical initiatives Staff/Principal Level (8+ years) Technical leadership experience with complex perception systems Deep expertise across multiple vision domains (2D/3D, classical/learning-based) Strategic thinking about perception architecture and technology roadmaps Track record of building and scaling high-performance computer vision teams Preferred Qualifications Experience with agricultural or outdoor computer vision applications Knowledge of 3D sensors (stereo cameras, LiDAR, structured light) GPU programming skills (CUDA) for accelerating vision algorithms Experience with vision-language models or foundation models Familiarity with ROS2 for perception system integration Publications at top-tier computer vision conferences (CVPR, ICCV, ECCV) Open source contributions to computer vision projects Why Eternal? Launch Your Career : For new graduates, this is a unique opportunity to join a proven team and learn from engineers who've already built and deployed commercial vision systems. You'll get hands-on experience with cutting-edge technology while making a real-world impact from day one. Impact at Scale : Your perception algorithms will directly enable robots to transform 800,000 hectares of greenhouses worldwide into sustainable, autonomous food production facilities. Technical Excellence : Work with state-of-the-art computer vision technology including modern deep learning architectures, 3D perception, and multi-modal sensor fusion. Rapid Innovation : Our software-first approach means you'll see your models deployed to real robots in hours/days, not months. We've proven we can develop and deploy new perception capabilities over-the-air as crops evolve. Unique Challenges : Tackle perception problems that combine the complexity of outdoor vision (varying lighting, weather) with the precision requirements of industrial automation. Growth Opportunity : Join as we scale from proof-of-concept to global deployment. Be part of the core team shaping the future of agricultural perception. Clear career progression from graduate to senior engineer and beyond. Mentorship & Learning : Work alongside experienced computer vision engineers who've solved complex real-world problems. We invest in your growth through hands-on projects, technical mentorship, and exposure to all aspects of vision system development. Flexible Work Culture : Distributed team with offices in Cologne and Bengaluru, following a "follow-the-sun" support model for our 24/7 operations. Our Tech Stack Vision Libraries : OpenCV, PCL, Open3D Deep Learning : PyTorch, TensorFlow, ONNX Deployment : TensorRT, OpenVINO, ONNX Runtime Sensors : RGB cameras, stereo vision, depth sensors Infrastructure : Cloud-native training pipelines, edge deployment systems Integration : ROS2 for robotic system integration Apply Now Ready to revolutionize how the world grows food through advanced computer vision? Whether you're starting your career or looking to make a bigger impact, join us in building perception systems that will enable sustainable food production for billions. We're committed to building a diverse and inclusive team. We encourage applications from candidates of all backgrounds and experience levels who are excited about our mission and show potential to grow with us. Recent graduates - don't let experience requirements hold you back; we value passion, potential, and fresh perspectives. Eternal is building unmanned food production sites that can sustainably produce fresh food year-round. Backed by world-class investors and partnering with leading agricultural companies, we're turning the vision of fully-autonomous unmanned greenhouses into reality.

AI Intern – Model Fine-Tuning, Video Intelligence, and Multilingual Media Tech Location: Remot e / India Duration: 3–6 Months Start: Immediate About Us We are a fast-moving tech team building cutting-edge solutions at the intersection of AI, video intelligence, and multilingual media. We’re now looking for AI Interns who are excited about working hands-on with the latest open-source models and taking them from prototype to production. This is your chance to build real-world, production-grade AI systems—not just toy models. If you love experimenting, optimizing, and seeing your work go live, you’ll love working with us. What You’ll Work On As an intern, you’ll help us build intelligent pipelines that: 🎬 Convert long-form videos into engaging short reels 📝 Auto-generate subtitles from video/audio 🌐 Translate video content into multiple languages (text + speech) 🗣️ Add dubbed audio with emotional tone matching across language s To achieve this, you’ll : Fine-tune and evaluate open-source AI models (Hugging Face, etc. ) Work with speech-to-text (STT), text-to-text (translation), and text-to-speech (TTS) system s Optimize models for real-time inference using tools like ONNX, quantization, etc . Collaborate closely with engineers to integrate AI into full-stack pipeline s Who We’re Looking Fo rStrong programming skills in C (essential for performance-critical modules ) Working knowledge of Python, PyTorch, Transformers, or similar framework s Basic understanding of model training, fine-tuning, and inference workflow s Hunger to learn, build, and solve open-ended problem s (Bonus) Familiarity with video/audio libraries (FFmpeg, OpenCV), Docker, or REST API s Why Join U s✅ Work on impactful, real-world AI project s✅ Get hands-on mentorship in applied AI & production engineerin g✅ See your work ship and make a differenc e✅ Flexible, remote-friendly work setu p Ready to apply ?Send your resume, GitHub/portfolio (if any), and a short note about why this excites you to hr@mantechventures.com . Show more Show less

Job Title: AI Developer Working Hours: 10 AM – 4 PM UTC+3) About Us: Headquartered in Sunnyvale, with offices in Dallas & Hyderabad, Fission Labs is a leading software development company, specializing in crafting flexible, agile, and scalable solutions that propel businesses forward. With a comprehensive range of services, including product development, cloud engineering, big data analytics, QA, DevOps consulting, and AI/ML solutions, we empower clients to achieve sustainable digital transformation that aligns seamlessly with their business goals. About the Role: We are seeking a highly skilled AI Developer to join our specialized team focused on developing and benchmarking on-device AI solutions for MacOS and Windows platforms. The ideal candidate will have deep technical expertise in local inference, AI model optimization, and device-level benchmarking, particularly on Apple Silicon using CoreML and MLX. You will work on creating benchmarks for local LLMs and computer vision models, optimize them across a range of hardware accelerators, and contribute to the development of robust performance evaluation frameworks for future hardware platforms. Responsibilities: Develop and maintain on-device AI benchmarks for MacOS using the MLX framework. Port existing LLM benchmarks (phi, Mistral, LLaMA2/3) from Windows to MacOS. Create CoreML versions of selected computer vision models and perform quantization for various data types and hardware targets (CPU, GPU, Neural Engine). Design and prototype local fine-tuning benchmarks, including data preparation, parameter selection, and training strategy evaluation. Work with on-device AI accelerators (e.g., Apple CoreML, ONNX Runtime, TensorRT, OpenVINO, SNPE). Maintain, extend, and optimize benchmarks for future and unreleased hardware platforms across Windows, Mac, mobile, and embedded devices. Collaborate with hardware and software teams to refine benchmark design and test coverage. Analyze model performance, document findings, and suggest optimization strategies. Communicate progress and findings effectively in English to internal stakeholders. Required Skills & Experience: Strong coding expertise in Python, C++, and C. Deep understanding of deep learning frameworks: TensorFlow, PyTorch. Experience working with local/on-device inference engines such as: Apple CoreML (preferred) ONNX Runtime NVIDIA TensorRT Intel OpenVINO Qualcomm SNPE Familiarity with open-source model repositories like Hugging Face. Proven experience in all stages of the software development lifecycle – from prototyping to optimization. Solid debugging and problem-solving skills. Excellent communication skills in English. Qualifications: Bachelor’s degree in computer science or related field. Minimum of 5 years' experience in software design and development. Demonstrated experience in AI model development and deployment. We Offer: Opportunity to work on impact-full technical challenges with global reach. Vast opportunities for self-development, including online university access and knowledge sharing opportunities. Sponsored Tech Talks & Hackathons to foster innovation and learning. Generous benefits package including health insurance, retirement benefits, flexible work hours, and more. Supportive work environment with forums to explore passions-beyond work. This role presents unique opportunity to contribute to the future of impact-full business solutions while advancing your career in a collaborative and innovative environment. Show more Show less

Job Listing Detail Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps. Your role in our mission Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation. What we're looking for Bachelor's/Master’s degree in computer science, Engineering, or related fields. Strong experience with ML Ops tools (Kubeflow, MLflow, TFX, SageMaker, etc.). Experience with LLM-specific tools and frameworks (LangChain,Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. Proficient in containerization (Docker, Kubernetes) and CI/CD practices. Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. Strong skills in Giskard, Deepeval etc. What you should expect in this role Fully Remote Opportunity – Work from anywhere in the India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. Show more Show less

About the Role: We are looking for a passionate and driven AI/ML Engineer with hands-on experience or strong interest in working with Large Language Models (LLMs), fine-tuning techniques, and LangChain framework integration. You will be responsible for building and optimizing intelligent agents, RAG pipelines, and dynamic workflows tailored for real-world applications in the blockchain and AI automation space. Key Responsibilities: Fine-tune and train Large Language Models (LLMs) using open-source frameworks and proprietary datasets. Develop and deploy LangChain-based intelligent agents for custom workflows (RAG, Tool Calling, Memory). Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Chroma, Weaviate, or Qdrant. Work with Hugging Face Transformers, OpenAI/Anthropic APIs, and other foundation model platforms. Integrate prompt engineering techniques to enhance model outputs for agent tasks. Optimize training datasets and workflows for efficiency, accuracy, and scalability. Collaborate with backend teams to deploy models in containerized environments (Docker, FastAPI). Monitor performance metrics and continuously improve the models. Required Skills: Strong understanding of Python and ML frameworks (PyTorch / TensorFlow). Familiarity with LLM APIs (OpenAI, Anthropic, Cohere, etc.) Hands-on experience or knowledge of LangChain and/or LangGraph. Experience in vector database integration for RAG pipelines. Basic knowledge of prompt engineering and model inference logic. Exposure to training or fine-tuning transformer-based models. Nice to Have: Experience with model quantization (GGUF/GGML), LoRA, PEFT, or QLoRA. Exposure to Hugging Face ecosystem, including model hub and datasets. Experience with cloud infrastructure (AWS/GCP), Kubernetes, or GPU clusters. Familiarity with MLOps and model versioning practices. Qualifications: B.Tech / M.Tech / B.Sc / M.Sc in Computer Science, AI, Data Science, or equivalent. Project portfolio, GitHub repo, or published demos is a plus (mention in resume). Job Types: Full-time, Permanent Pay: ₹50,000.00 - ₹80,000.00 per month Schedule: Day shift Fixed shift Work Location: In person

Duration: 12 Months Location: PAN INDIA Timings: Full Time (As per company timings) Notice Period: within 15 days or immediate joiner Experience: 0-3 Years Work type: Full-time We are looking for a Machine Learning Engineer to help us deploy, configure, and optimize Mistral 7B , integrate it into our services, and implement Retrieval-Augmented Generation (RAG) for database interactions. Key Responsibilities Configure and optimize Mistral 7B for business tasks (fine-tuning, quantization, performance optimization). Assess required computational resources, select the optimal infrastructure for model deployment (on-premise or cloud), and analyse cost efficiency. Implement RAG to integrate models with vector databases. Orchestrate interactions between multiple ML services (e.g., one model generates tags, and another validates task descriptions). Develop a service for interacting with the model (API for predictions, model management, integration with our application). Optimize model performance for real-world usage. Requirements Experience with LLM models (Mistral 7B, GPT-3/4, LLaMA, Claude, Falcon, Bloom, etc.). Understanding of Retrieval-Augmented Generation (RAG) and model integration with databases. Hands-on experience with fine-tuning and dataset preparation/annotation. Experience with vector databases (Pinecone, Weaviate, FAISS). Strong proficiency in Python and libraries like PyTorch, TensorFlow, Hugging Face, and LangChain. Experience in evaluating and optimizing infrastructure for AI deployments. Experience in developing APIs for integrating AI models into business processes. Show more Show less

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way. The Role : In this role you will be part of the Logitech Hardware Audio DSP and ML team developing and will be implementing real-time audio ML solutions to deliver innovative audio experiences to the customer. If you have a strong understanding of Audio DSP and TinyML apply for this role and have a huge contribution on the audio products that we develop! Your Contribution: Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will: Responsible for developing model and inference on resource constrained platforms like Tensilica DSP, ARM and RISCV cores. Responsible for optimizing and improving algorithm performance in real-world conditions – demonstrating innovative solutions to tough challenges. Work with cross-functional product team to deliver seamless customer audio experience. Key Qualifications: For consideration, you must bring the following minimum skills and experiences to our team: Experience leading a ML team with 10+ years of experience working in audio signal processing/ML. Tiny ML / Embedded ML - Hands-on experience porting neural network algorithms from intermediate representations such as Tensor Flow (TFLM), ONNX, etc. onto embedded targets using device-specific compilation tools and/or inference API’s. Deep understanding of on-device quantization techniques including post-training quantization, training-aware quantization, mixed precision inference. Strong programming skills in c, python. Conceptual understanding of how neural network operators map to embedded hardware accelerators such as DSP’s and NPU’s. Familiarity with Deep Learning Audio Signal Processing approaches for tasks including Speech enhancement / noise suppression / voice pickup Additional Skills: Experienced with Linux, Docker. Familiarity with CMSIS NN, HIFI NNLib is a plus Familiarity with audio measurements and standard subjective/objective audio evaluation metrics. Experience working in hardware product teams from product concept to mass production Good Audio listening skills and experience detecting audio artifacts. Experience communicating effectively in a cross functional environment. Strong problem-solving, critical-thinking skills Familiarity with code version control practices Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house. Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you! We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location. All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability. If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at +1-510-713-4866 for assistance and we will get back to you as soon as possible. Show more Show less

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way. The Role : In this role you will be part of the Logitech Hardware Audio DSP and ML team developing and will be implementing real-time audio ML solutions to deliver innovative audio experiences to the customer. If you have a strong understanding of Audio DSP and TinyML apply for this role and have a huge contribution on the audio products that we develop! Your Contribution: Be Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. Share our passion for Equality and the Environment. These are the behaviors and values you’ll need for success at Logitech. In this role you will : Responsible for developing model and inference on resource constrained platforms like Tensilica DSP, ARM and RISCV cores. Responsible for optimizing and improving algorithm performance in real-world conditions – demonstrating innovative solutions to tough challenges. Work with cross-functional product team to deliver seamless customer audio experience. Key Qualifications: For consideration, you must bring the following minimum skills and experiences to our team: 7+ years of experience working in audio signal processing product teams. Tiny ML / Embedded ML - Hands-on experience porting neural network algorithms from intermediate representations such as Tensor Flow (TFLM), ONNX, etc. onto embedded targets using device-specific compilation tools and/or inference API’s. Deep understanding of on-device quantization techniques including post-training quantization, training-aware quantization, mixed precision inference. Strong programming skills in c, python. Conceptual understanding of how neural network operators map to embedded hardware accelerators such as DSP’s and NPU’s. Familiarity with Deep Learning Audio Signal Processing approaches for tasks including Speech enhancement / noise suppression / voice pickup Additional Skills: Experienced with Linux, Docker. Familiarity with CMSIS NN, HIFI NNLib is a plus Familiarity with audio measurements and standard subjective/objective audio evaluation metrics. Experience working in hardware product teams from product concept to mass production Good Audio listening skills and experience detecting audio artifacts. Experience communicating effectively in a cross functional environment. Strong problem-solving, critical-thinking skills Familiarity with code version control practices Education: Minimum Engineering degree in EE, CS or equivalent practical experience. Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house. Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you! We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location. All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability. If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at +1-510-713-4866 for assistance and we will get back to you as soon as possible. Show more Show less

Company: Chicmic Studios Job Role: Python Machine Learning & AI Developer Experience Required: 3+ Years We are looking for a highly skilled and experienced Python Developer to join our dynamic team. The ideal candidate will have a robust background in developing web applications using Django and Flask, with expertise in deploying and managing applications on AWS. Proficiency in Django Rest Framework (DRF), a solid understanding of machine learning concepts, and hands-on experience with tools like PyTorch, TensorFlow, and transformer architectures are essential. Key Responsibilities Develop and maintain web applications using Django and Flask frameworks. Design and implement RESTful APIs using Django Rest Framework (DRF) Deploy, manage, and optimize applications on AWS services, including EC2, S3, RDS, Lambda, and CloudFormation. Build and integrate APIs for AI/ML models into existing systems. Create scalable machine learning models using frameworks like PyTorch , TensorFlow , and scikit-learn . Implement transformer architectures (e.g., BERT, GPT) for NLP and other advanced AI use cases. Optimize machine learning models through advanced techniques such as hyperparameter tuning, pruning, and quantization. Deploy and manage machine learning models in production environments using tools like TensorFlow Serving , TorchServe , and AWS SageMaker . Ensure the scalability, performance, and reliability of applications and deployed models. Collaborate with cross-functional teams to analyze requirements and deliver effective technical solutions. Write clean, maintainable, and efficient code following best practices. Conduct code reviews and provide constructive feedback to peers. Stay up-to-date with the latest industry trends and technologies, particularly in AI/ML. Required Skills and Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field. 3+ years of professional experience as a Python Developer. Proficient in Python with a strong understanding of its ecosystem. Extensive experience with Django and Flask frameworks. Hands-on experience with AWS services for application deployment and management. Strong knowledge of Django Rest Framework (DRF) for building APIs. Expertise in machine learning frameworks such as PyTorch , TensorFlow , and scikit-learn . Experience with transformer architectures for NLP and advanced AI solutions. Solid understanding of SQL and NoSQL databases (e.g., PostgreSQL, MongoDB). Familiarity with MLOps practices for managing the machine learning lifecycle. Basic knowledge of front-end technologies (e.g., JavaScript, HTML, CSS) is a plus. Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication skills and the ability to articulate complex technical concepts to non-technical stakeholders. Contact : 9875952836 Office Location: F273, Phase 8b Industrial Area Mohali, Punjab. Job Type: Full-time Schedule: Day shift Monday to Friday Work Location: In person

Build the AI Reasoning Layer for Education We’re reimagining the core intelligence layer for education—tackling one of the most ambitious challenges in AI: subjective assessment automation and ultra-personalized learning at scale. This isn’t just another LLM application. We’re building a first-principles AI reasoning engine combining multi-modal learning, dynamic knowledge graphs, and real-time content generation. The goal? To eliminate billions of wasted hours in manual evaluation and create an AI that understands how humans learn. As a Founding AI Engineer, you’ll define and build this system from the ground up. You’ll work on problems few have attempted, at the bleeding edge of LLMs, computer vision, and generative reasoning. What You’ll Be Solving: Handwriting OCR at near-human accuracy: How can we push vision-language models to understand messy, real-world input from students? Real-time learner knowledge modeling: Can AI track and reason about what someone knows—and how they’re learning—moment to moment? Generative AI that teaches: How do we create dynamic video lessons that evolve in sync with a learner’s knowledge state? Scalable inference infrastructure: How do we optimize LLMs and multimodal models to support millions of learners in real time? What You’ll Be Building: Architect, deploy & optimize multi-modal AI systems—OCR, knowledge-state inference, adaptive content generation. Build reasoning engines that combine LLMs, retrieval, and learner data to dynamically guide learning. Fine-tune foundation models (LLMs, VLMs) and implement cutting-edge techniques (quantization, LoRA, RAG, etc.). Design production-grade AI systems: modular, scalable, and optimized for inference at global scale. Lead experiments at the frontier of AI research, publishing if desired. Tech Stack & Skills Must-Have: Deep expertise in AI/ML, with a focus on LLMs, multi-modal learning, and computer vision. Hands-on experience with OCR fine-tuning and handwritten text recognition Strong proficiency in AI frameworks: PyTorch, TensorFlow, Hugging Face, OpenCV. Experience in optimizing AI for production: LLM quantization, retrieval augmentation, and MLOps. Knowledge graphs and AI-driven reasoning systems experience Desirable: Experience with Diffusion Models, Transformers, and Graph Neural Networks (GNNs). Expertise in vector databases, real-time inference pipelines, and low-latency AI deployment. Prior experience in ed-tech, adaptive learning AI, or multi-modal content generation. Why This Role Is Rare Define the AI stack for a category-defining product at inception. Work with deep ownership across research, engineering, and infrastructure. Founding-level equity and influence in a high-growth company solving a $100B+ problem. Balance of cutting-edge research and real-world deployment. Solve problems that matter—not just academically, but in people’s lives. Who this role is for builders at the edge—engineers who want to architect, not just optimize or Researchers who want their ideas shipped. This is you, if you want to: Push LLMs, CV, and multimodal models to their performance limits. Build AI that learns, reasons, and adapts like a human tutor. Shape the foundational AI layer for education Show more Show less

Key Responsibilities: Develop and Fine-Tune LLMs (e.g., GPT-4, Claude, LLaMA, Mistral, Gemini) using instruction tuning, prompt engineering, chain-of-thought prompting, and fine-tuning techniques. Build RAG Pipelines: Implement Retrieval-Augmented Generation solutions leveraging embeddings, chunking strategies, and vector databases like FAISS, Pinecone, Weaviate, and Qdrant. Implement and Orchestrate Agents: Utilize frameworks like MCP, OpenAI Agent SDK, LangChain, LlamaIndex, Haystack, and DSPy to build dynamic multi-agent systems and serverless GenAI applications. Deploy Models at Scale: Manage model deployment using HuggingFace, Azure Web Apps, vLLM, and Ollama, including handling local models with GGUF, LoRA/QLoRA, PEFT, and Quantization methods. Integrate APIs: Seamlessly integrate with APIs from OpenAI, Anthropic, Cohere, Azure, and other GenAI providers. Ensure Security and Compliance: Implement guardrails, perform PII redaction, ensure secure deployments, and monitor model performance using advanced observability tools. Optimize and Monitor: Lead LLMOps practices focusing on performance monitoring, cost optimization, and model evaluation. Work with AWS Services: Hands-on usage of AWS Bedrock, SageMaker, S3, Lambda, API Gateway, IAM, CloudWatch, and serverless computing to deploy and manage scalable AI solutions. Contribute to Use Cases: Develop AI-driven solutions like AI copilots, enterprise search engines, summarizers, and intelligent function-calling systems. Cross-functional Collaboration: Work closely with product, data, and DevOps teams to deliver scalable and secure AI products. Required Skills and Experience: Deep knowledge of LLMs and foundational models (GPT-4, Claude, Mistral, LLaMA, Gemini). Strong expertise in Prompt Engineering, Chain-of-Thought reasoning, and Fine-Tuning methods. Proven experience building RAG pipelines and working with modern vector stores ( FAISS, Pinecone, Weaviate, Qdrant ). Hands-on proficiency in LangChain, LlamaIndex, Haystack, and DSPy frameworks. Model deployment skills using HuggingFace, vLLM, Ollama, and handling LoRA/QLoRA, PEFT, GGUF models. Practical experience with AWS serverless services: Lambda, S3, API Gateway, IAM, CloudWatch. Strong coding ability in Python or similar programming languages. Experience with MLOps/LLMOps for monitoring, evaluation, and cost management. Familiarity with security standards: guardrails, PII protection, secure API interactions. Use Case Delivery Experience: Proven record of delivering AI Copilots, Summarization engines, or Enterprise GenAI applications. Experience 6-8 years of experience in AI/ML roles, focusing on LLM agent development, data science workflows, and system deployment. Demonstrated experience in designing domain-specific AI systems and integrating structured/unstructured data into AI models. Proficiency in designing scalable solutions using LangChain and vector databases. Job Type: Full-time Pay: ₹2,000,000.00 - ₹3,000,000.00 per year Benefits: Health insurance Schedule: Monday to Friday Work Location: In person

Job Description Be part of the solution at Technip Energies and embark on a one-of-a-kind journey. You will be helping to develop cutting-edge solutions to solve real-world energy problems. About us: Technip Energies is a global technology and engineering powerhouse. With leadership positions in LNG, hydrogen, ethylene, sustainable chemistry, and CO2 management, we are contributing to the development of critical markets such as energy, energy derivatives, decarbonization, and circularity. Our complementary business segments, Technology, Products and Services (TPS) and Project Delivery, turn innovation into scalable and industrial reality. Through collaboration and excellence in execution, our 17,000+ employees across 34 countries are fully committed to bridging prosperity with sustainability for a world designed to last. About the role: We are currently seeking an AI Solution Architect , to join our team based in Noida. Key Responsibilities Design and architect enterprise-grade AI solutions with emphasis on transformer architectures and generative AI systems Develop and implement strategies for training, fine-tuning, and deploying open-source LLMs (Large Language Models) Implement cost-efficient and low-latency architectures for LLM inference services Build secure API frameworks for generative AI data transmission, processing, and reception Design optimized pipelines for processing multimodal data including text, images, and video for vector embeddings Lead technical discovery sessions with stakeholders to translate business requirements into AI solution designs Create detailed technical specifications, reference architectures, and implement roadmaps Engineer scalable solutions capable of handling increased request volumes and data storage needs Develop MVPs from proof-of-concepts, accelerating the development of the lifecycle of AI products Provide technical leadership for AI development teams using agile methodologies About you: 8+ years of experience in software development with at least 5 years focused on AI/ML solutions Extensive experience with transformer-based models (Anthropic, GPT, T5, LLaMA, Mistral) and generative AI technologies Proven expertise in fine-tuning and deploying open-source LLMs for production environments Deep knowledge of vector databases (Pinecone, Weaviate, Milvus, FAISS) and retrievalaugmented generation Strong proficiency in the Azure AI ecosystem, including Azure OpenAI Service, Azure Machine Learning, and Azure Cognitive Services Experience with LLM optimization techniques including quantization, distillation, and prompt engineering Expertise in designing and implementing secure API frameworks with JWT, OAuth, and API gateways Demonstrated ability to create low-latency, high-throughput AI systems using efficient orchestration Hands-on experience with containerization (Docker), orchestration (Kubernetes), and microservices architectures Proficiency in Python and AI frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, and LangChain Experience with MLOps practices and CI/CD pipelines for model deployment and monitoring Strategic thinking to align AI solutions with broader business objectives and customer needs Collaborative approach to problem-solving with adaptability to rapidly evolving technologies Preferred Qualifications Experience with multi-modal AI systems integrating vision and language capabilities Knowledge of embedding models (CLIP, SBERT, Ada) and their applications Expertise in RAG (Retrieval-Augmented Generation) architecture and implementations Experience with Azure Kubernetes Service (AKS) for model deployment Familiarity with vector search optimization and semantic caching strategies Background in implementing AI guardrails and safety measures for generative AI systems Experience with streaming inference and real-time AI processing Knowledge of distributed training techniques and infrastructure Expertise in GPU/TPU utilization optimization for AI workloads Experience with enterprise data governance and compliance requirements for AI systems Creative perspective for presenting AI strategies and roadmaps to stakeholders with illustrative flow diagrams & engaging content Customer-focused mindset with emphasis on delivering tangible business outcomes Intellectual curiosity and passion for staying current with emerging AI technologies and implementing PoC level solutions to accelerate and inculcate these solutions in development team. Your career with us: Working at Technip Energies is an inspiring journey, filled with groundbreaking projects and dynamic collaborations. Surrounded by diverse and talented individuals, you will feel welcomed, respected, and engaged. Enjoy a safe, caring environment where you can spark new ideas, reimagine the future, and lead change. As your career grows, you will benefit from learning opportunities at T.EN University, such as The Future Ready Program, and from the support of your manager through check-in moments like the Mid-Year Development Review, fostering continuous growth and development What’s next? Once receiving your application, our Talent Acquisition professionals will screen and match your profile against the role requirements. We ask for your patience as the team completes the volume of applications with reasonable timeframe. Check your application progress periodically via personal account from created candidate profile during your application. 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Build the AI Reasoning Layer for Education We’re reimagining the core intelligence layer for education —tackling one of the most ambitious challenges in AI: subjective assessment automation and ultra-personalized learning at scale. This isn’t just another LLM application. We’re building a first-principles AI reasoning engine combining multi-modal learning, dynamic knowledge graphs, and real-time content generation . The goal? To eliminate billions of wasted hours in manual evaluation and create an AI that understands how humans learn . As a Founding AI Engineer , you’ll define and build this system from the ground up. You’ll work on problems few have attempted, at the bleeding edge of LLMs, computer vision, and generative reasoning. What You’ll Be Solving: Handwriting OCR at near-human accuracy: How can we push vision-language models to understand messy, real-world input from students? Real-time learner knowledge modeling: Can AI track and reason about what someone knows—and how they’re learning—moment to moment? Generative AI that teaches: How do we create dynamic video lessons that evolve in sync with a learner’s knowledge state? Scalable inference infrastructure: How do we optimize LLMs and multimodal models to support millions of learners in real time? What You’ll Be Building: Architect, deploy & optimize multi-modal AI systems—OCR, knowledge-state inference, adaptive content generation. Build reasoning engines that combine LLMs, retrieval, and learner data to dynamically guide learning. Fine-tune foundation models (LLMs, VLMs) and implement cutting-edge techniques (quantization, LoRA, RAG, etc.). Design production-grade AI systems: modular, scalable, and optimized for inference at global scale. Lead experiments at the frontier of AI research, publishing if desired. Tech Stack & Skills Must-Have: Deep expertise in AI/ML, with a focus on LLMs, multi-modal learning, and computer vision. Hands-on experience with OCR fine-tuning and handwritten text recognition Strong proficiency in AI frameworks: PyTorch, TensorFlow, Hugging Face, OpenCV. Experience in optimizing AI for production: LLM quantization, retrieval augmentation, and MLOps. Knowledge graphs and AI-driven reasoning systems experience Nice-to-Have: Experience with Diffusion Models, Transformers, and Graph Neural Networks (GNNs). Expertise in vector databases, real-time inference pipelines, and low-latency AI deployment. Prior experience in ed-tech, adaptive learning AI, or multi-modal content generation. Why This Role Is Rare Define the AI stack for a category-defining product at inception. Work with deep ownership across research, engineering, and infrastructure. Founding-level equity and influence in a high-growth company solving a $100B+ problem. Balance of cutting-edge research and real-world deployment. Solve problems that matter —not just academically, but in people’s lives. Who this role is for This is for builders at the edge—engineers who want to architect, not just optimize. Researchers who want their ideas shipped.If you want to: Push LLMs, CV, and multimodal models to their performance limits. Build AI that learns, reasons, and adapts like a human tutor. Shape the foundational AI layer for education Show more Show less

It's fun to work in a company where people truly BELIEVE in what they are doing! We're committed to bringing passion and customer focus to the business. Job Description About Fractal What makes Fractal a GREAT fit for you? When you join Fractal, you’ll be part of a fast-growing team that helps our clients leverage AI together with the power of behavioural sciences to make better decisions. We’re a strategic analytics partner to most admired fortune 500 companies globally, we help them power every human decision in the enterprise by bringing analytics, AI and behavioural science to the decision. Our people enjoy a collaborative work environment, exceptional training and career development — as well as unlimited growth opportunities. We have a Glassdoor rating of 4 / 5 and achieve customer NPS of 9/ 10. If you like working with a curious, supportive, high-performing team, Fractal is the place for you. close. Responsibilities Design and implement advanced solutions utilizing Large Language Models (LLMs). Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. Conduct research and stay informed about the latest developments in generative AI and LLMs. Develop and maintain code libraries, tools, and frameworks to support generative AI development. Participate in code reviews and contribute to maintaining high code quality standards. Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. Possess strong analytical and problem-solving skills. Demonstrate excellent communication skills and the ability to work effectively in a team environment. Primary Skills Natural Language Processing (NLP): Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. Computer Vision and Audio: Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. Generative AI: Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization. Cloud: Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git. Tech Skills (10+ Years’ Experience): Machine Learning (ML) & Deep Learning Solid understanding of supervised and unsupervised learning. Proficiency with deep learning architectures like Transformers, LSTMs, RNNs, etc. Generative AI: Hands-on experience with models such as OpenAI GPT4, Anthropic Claude, LLama etc. Knowledge of fine-tuning and optimizing large language models (LLMs) for specific tasks. Natural Language Processing (NLP): Expertise in NLP techniques, including text preprocessing, tokenization, embeddings, and sentiment analysis. Familiarity with NLP tasks such as text classification, summarization, translation, and question-answering. Retrieval-Augmented Generation (RAG): In-depth understanding of RAG pipelines, including knowledge retrieval techniques like dense/sparse retrieval. Experience integrating generative models with external knowledge bases or databases to augment responses. Data Engineering: Ability to build, manage, and optimize data pipelines for feeding large-scale data into AI models. Search and Retrieval Systems: Experience with building or integrating search and retrieval systems, leveraging knowledge of Elasticsearch, AI Search, ChromaDB, PGVector etc. Prompt Engineering: Expertise in crafting, fine-tuning, and optimizing prompts to improve model output quality and ensure desired results. Understanding how to guide large language models (LLMs) to achieve specific outcomes by using different prompt formats, strategies, and constraints. Knowledge of techniques like few-shot, zero-shot, and one-shot prompting, as well as using system and user prompts for enhanced model performance. Programming & Libraries: Proficiency in Python and libraries such as PyTorch, Hugging Face, etc. Knowledge of version control (Git), cloud platforms (AWS, GCP, Azure), and MLOps tools. Database Management: Experience working with SQL and NoSQL databases, as well as vector databases APIs & Integration: Ability to work with RESTful APIs and integrate generative models into applications. Evaluation & Benchmarking: Strong understanding of metrics and evaluation techniques for generative models. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us! Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest! Show more Show less

Compiler Lead Hyderabad Founded by highly respected Silicon Valley veterans - with its design centers established in Santa Clara, California. / Hyderabad/Bangalore A US based well-funded product-based startup looking for Highly talented Verification Engineers for the following roles. We are looking for a highly experienced systems engineer with deep expertise in compilers, machine learning infrastructure, and system-level performance optimization. This role is hands-on and research-driven, ideal for someone who thrives on solving low-level performance challenges and building core infrastructure that powers next-generation AI workloads. Key Responsibilities: Compiler Design & Optimization Develop and enhance compiler toolchains based on LLVM, MLIR, Open64, or Glow. Build and optimize intermediate representations, custom dialects, and code generation flows for AI accelerators. Implement transformations and optimizations for latency, memory usage, and compute efficiency. AI System Integration Work closely with hardware teams to co-design compilers targeting custom silicon. Integrate compiler backends with ML frameworks like PyTorch, TensorFlow, or ONNX. Build graph-level and kernel-level transformations for AI training and inference pipelines. Performance Tuning & System Analysis Conduct low-level profiling and performance tuning across compiler and runtime layers. Identify and eliminate bottlenecks across CPU/GPU/NPU workloads. Develop parallel programming solutions leveraging SIMD, multi-threading, and heterogeneous computing. Tooling & Infrastructure Develop tooling for performance analysis, debug, and test automation. Contribute to internal SDKs and devkits used by AI researchers and system engineers. Required Skills & Experience: Strong compiler development experience using LLVM, MLIR, Glow, or similar toolchains. Proficiency in C/C++, with solid command of Python for tooling and automation. In-depth understanding of compiler internals, including IR design, lowering, codegen, and scheduling. Deep knowledge of hardware-software co-design, particularly for AI/ML workloads. Experience with runtime systems, memory models, and performance modeling. Solid grasp of parallel and heterogeneous computing paradigms. Nice to Have: Experience working with custom AI hardware or edge inference platforms. Familiarity with quantization, scheduling for dataflow architectures, or compiler autotuning. Contributions to open-source compiler projects (e.g., LLVM, MLIR, TVM). Qualifications: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field. 8–15 years of relevant hands-on experience in compilers, systems programming, or AI infrastructure. Contact: Uday Mulya Technologies muday_bhaskar@yahoo.com "Mining The Knowledge Community" Show more Show less

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Job Description More Details Below: Join The Exciting Generative AI Team At Qualcomm Focused On Integrating Cutting Edge GenAI Models On Qualcomm Chipsets. The Team Uses Qualcomm Chips’ Extensive Heterogeneous Computing Capabilities To Allow Inference Of GenAI Models On-Device Without A Need For Connection To The Cloud. Our Inference Engine Is Designed To Help Developers Run Neural Network Models Trained In A Variety Of Frameworks On Snapdragon Platforms At Blazing Speeds While Still Sipping The Smallest Amount Of Power. Utilize This Power Efficient Hardware And Software Stack To Run Large Language Models (LLMs) And Large Vision Models (LVM) At Near GPU Speeds! Responsibilities: In This Role, You Will Spearhead The Development And Commercialization Of The Qualcomm AI Runtime (QAIRT) SDK On Qualcomm SoCs. As An AI Inferencing Expert, You'll Push The Limits Of Performance From Large Models. Your Mastery In Deploying Large C/C++ Software Stacks Using Best Practices Will Be Essential. You'll Stay On The Cutting Edge Of GenAI Advancements, Understanding LLMs/Transformers And The Nuances Of Edge-Based GenAI Deployment. Most Importantly, Your Passion For The Role Of Edge In AI's Evolution Will Be Your Driving Force. Requirements: Master’s/Bachelor’s Degree In Computer Science Or Equivalent. 3+ Years Of Relevant Work Experience In Software Development. Strong Understanding Of Generative AI Models – LLM, LVM And LLMs And Building Blocks Floating-Point, Fixed-Point Representations And Quantization Concepts. Experience With Optimizing Algorithms For AI Hardware Accelerators (Like CPU/GPU/NPU). Strong Development Skills In C/C++ Excellent Analytical And Debugging Skills. Good Communication Skills (Verbal, Presentation, Written). Ability To Collaborate Across A Globally Diverse Team And Multiple Interests. Preferred Qualifications Strong Understanding Of SIMD Processor Architecture And System Design. Proficiency In Object-Oriented Software Development. Familiarity With Linux And Windows Environment Strong Background In Kernel Development For SIMD Architectures. Familiarity With Frameworks Like Llama.Cpp, MLX, And MLC Is A Plus. Good Knowledge Of PyTorch, TFLite, And ONNX Runtime Is Preferred. Experience With Parallel Computing Systems And Assembly Is A Plus. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Qualcomm's Corporate Engineering division in Chennai is looking for software tools development engineer. The candidate will work in a development role to put together software for tool development and test automation across various technologies that are part of Access points, mobile platform, RF, Machine learning platforms. The candidate is expected to have full proficiency on C++ or C# or Python and have experience on developing applications, APIs, software automation using a combination of commercial test equipment and custom hardware designs. The ideal candidate will be responsible for implementing novel test plans and supporting those test plans from the R&D lab environment through manufacturing. Candidate will also be responsible for evaluating new complex hardware designs and providing feedback regarding design for testability. Candidate will be responsible to own the test infrastructure, build automation framework and enable other developers towards achieving deployable, scalable test frameworks. Candidate will be responsible for implementing automated test solutions for those hardware designs using a combination of custom test software/hardware and commercial test equipment. The candidate will interface with internal staff and outside partners in the fast-paced execution of a variety of multi-disciplined projects. The candidate will have an opportunity to influence and help adopt new test, tool development methodologies and enhance existing processes. International travel might be required. All Qualcomm employees are expected to actively support diversity on their teams, and in the Company. Minimum Qualifications: B.E/B.Tech. with industry experience in the following areas: 2+ years of programming experience across C++ / C# / Python Strong lab skills and experience with standard lab equipment is required Strong experience in various software technologies, methodologies and applied software engineering practices/standards such as Object-Oriented Design (OOD), cloud and embedded software test automation Preferred Qualifications: Strong programming skills in C++/C# Experience with embedded software and device drivers Application UI design Winforms/WPF Experience with hardware debug equipment such as JTAG and scope Experience with scripting languages (Perl, Python etc.) Familiarity with AI frameworks models performance, quantization, and accuracy metrics Good analytical, debug and problem-solving abilities Good communication skills and ability to work in a cross-functional team environment Effectively delegates tasks to other team members, multitasks and meets aggressive schedules in a dynamic environment. FPGA/CPLD design, JTAG/boundary scan Experience with RF test equipment measurements such as signal generator and spectrum analyzer and HW/SW issue troubleshooting Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Education requirements: Required: B.E. or B.Tech. in Electronics and Communication or Electrical engineering or Computer Science or equivalent. Preferred: Masters Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Redefine the future of customer experiences. One conversation at a time. We're changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you're ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you're in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities: Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications: Education: Master's degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills: MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes: Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you're passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security - Provident Fund & Gratuity Wellness ‍ - Employee Assistance Program and comprehensive wellness initiatives Growth - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what's going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. #LI-SC1 #LI-Hybrid

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications Education: Master’s degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you’re passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications Education: Master’s degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you’re passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less