153 Quantization Jobs - Page 5

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 Title: Data Scientist/Senior Data Scientist Location: Bangalore/Mumbai/Gurgaon/Chennai/Pune/Noida/Hyderabad 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. AND/OR 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. 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

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 Title: Data Scientist/Senior Data Scientist Location: Bangalore/Mumbai/Gurgaon/Chennai/Pune/Noida/Hyderabad 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. AND/OR 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. 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

Applied Machine Learning Scientist – Voice AI, NLP & GenAI Applications Location : Sector 63, Gurugram, Haryana – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM – 8:00 PM Experience : 3–7 years in applied ML, with at least 2 years focused on voice, NLP, or GenAI deployments Function : AI/ML Research & Engineering | Conversational Intelligence | Real-time Model Deployment Apply : careers@darwix.ai Subject Line : “Application – Applied ML Scientist – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform transforming how enterprise sales, support, and credit teams engage with customers. Our proprietary AI stack ingests data across calls, chat, email, and CCTV streams to generate: Real-time nudges for agents and reps Conversational analytics and scoring to drive performance CCTV-based behavior insights to boost in-store conversion We’re live across leading enterprises in India and MENA, including IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar , and others. We’re backed by top-tier operators and venture investors and scaling rapidly across multiple verticals and geographies. Role Overview We are looking for a hands-on, impact-driven Applied Machine Learning Scientist to build, optimize, and productionize AI models across ASR, NLP, and LLM-driven intelligence layers . This is a core role in our AI/ML team where you’ll be responsible for building the foundational ML capabilities that drive our real-time sales intelligence platform. You will work on large-scale multilingual voice-to-text pipelines, transformer-based intent detection, and retrieval-augmented generation systems used in live enterprise deployments. Key ResponsibilitiesVoice-to-Text (ASR) Engineering Deploy and fine-tune ASR models such as WhisperX, wav2vec 2.0, or DeepSpeech for Indian and GCC languages Integrate diarization and punctuation recovery pipelines Benchmark and improve transcription accuracy across noisy call environments Optimize ASR latency for real-time and batch processing modes NLP & Conversational Intelligence Train and deploy NLP models for sentence classification, intent tagging, sentiment, emotion, and behavioral scoring Build call scoring logic aligned to domain-specific taxonomies (sales pitch, empathy, CTA, etc.) Fine-tune transformers (BERT, RoBERTa, etc.) for multilingual performance Contribute to real-time inference APIs for NLP outputs in live dashboards GenAI & LLM Systems Design and test GenAI prompts for summarization, coaching, and feedback generation Integrate retrieval-augmented generation (RAG) using OpenAI, HuggingFace, or open-source LLMs Collaborate with product and engineering teams to deliver LLM-based features with measurable accuracy and latency metrics Implement prompt tuning, caching, and fallback strategies to ensure system reliability Experimentation & Deployment Own model lifecycle: data preparation, training, evaluation, deployment, monitoring Build reproducible training pipelines using MLflow, DVC, or similar tools Write efficient, well-structured, production-ready code for inference APIs Document experiments and share insights with cross-functional teams Required Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields 3–7 years experience applying ML in production, including NLP and/or speech Experience with transformer-based architectures for text or audio (e.g., BERT, Wav2Vec, Whisper) Strong Python skills with experience in PyTorch or TensorFlow Experience with REST APIs, model packaging (FastAPI, Flask, etc.), and containerization (Docker) Familiarity with audio pre-processing, signal enhancement, or feature extraction (MFCC, spectrograms) Knowledge of MLOps tools for experiment tracking, monitoring, and reproducibility Ability to work collaboratively in a fast-paced startup environment Preferred Skills Prior experience working with multilingual datasets (Hindi, Arabic, Tamil, etc.) Knowledge of diarization and speaker separation algorithms Experience with LLM APIs (OpenAI, Cohere, Mistral, LLaMA) and RAG pipelines Familiarity with inference optimization techniques (quantization, ONNX, TorchScript) Contribution to open-source ASR or NLP projects Working knowledge of AWS/GCP/Azure cloud platforms What Success Looks Like Transcription accuracy improvement ≥ 85% across core languages NLP pipelines used in ≥ 80% of Darwix AI’s daily analyzed calls 3–5 LLM-driven product features delivered in the first year Inference latency reduced by 30–50% through model and infra optimization AI features embedded across all Tier 1 customer accounts within 12 months Life at Darwix AI You will be working in a high-velocity product organization where AI is core to our value proposition. You’ll collaborate directly with the founding team and cross-functional leads, have access to enterprise datasets, and work on ML systems that impact large-scale, real-time operations. We value rigor, ownership, and speed. Model ideas become experiments in days, and successful experiments become deployed product features in weeks. Compensation & Perks Competitive fixed salary based on experience Quarterly/Annual performance-linked bonuses ESOP eligibility post 12 months Compute credits and model experimentation environment Health insurance, mental wellness stipend Premium tools and GPU access for model development Learning wallet for certifications, courses, and AI research access Career Path Year 1: Deliver production-grade ASR/NLP/LLM systems for high-usage product modules Year 2: Transition into Senior Applied Scientist or Tech Lead for conversation intelligence Year 3: Grow into Head of Applied AI or Architect-level roles across vertical product lines How to Apply Email the following to careers@darwix.ai : Updated resume (PDF) A short write-up (200 words max): “How would you design and optimize a multilingual voice-to-text and NLP pipeline for noisy call center data in Hindi and English?” Optional: GitHub or portfolio links demonstrating your work Subject Line : “Application – Applied Machine Learning Scientist – [Your Name]” Show more Show less

Head of AI & ML Platforms Focus : Voice AI, NLP, Conversation Intelligence for Omnichannel Enterprise Sales Location : Sector 63, Gurugram, Haryana — Full-time, 100% In-Office Work Hours : 10:30 AM – 8:00 PM, Monday to Friday (2nd and 4th Saturdays off) Experience Required : 8–15 years in AI/ML, with 3+ years leading teams in voice, NLP, or conversation platforms Apply : careers@darwix.ai Subject Line : “Application – Head of AI & ML Platforms – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform for enterprise revenue teams across sales, support, credit, and retail. Our proprietary AI stack ingests multimodal inputs—voice calls, chat logs, emails, and CCTV streams—and delivers contextual nudges, conversation scoring, and performance analytics in real time. Our suite of products includes: Transform+ : Real-time conversational intelligence for contact centers and field sales Sherpa.ai : A multilingual GenAI assistant that provides in-the-moment coaching, summaries, and objection handling support Store Intel : A computer vision solution that transforms CCTV feeds into actionable insights for physical retail spaces Darwix AI is trusted by large enterprises such as IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar, and Sobha Realty , and is backed by leading institutional and operator investors. We are expanding rapidly across India, the Middle East, and Southeast Asia. Role Overview We are seeking a highly experienced and technically strong Head of AI & ML Platforms to architect and lead the end-to-end AI systems powering our voice intelligence, NLP, and GenAI solutions. This is a leadership role that blends research depth with applied engineering execution. The ideal candidate will have deep experience in building and deploying voice-to-text pipelines, multilingual NLP systems, and production-grade inference workflows. The individual will be responsible for model design, accuracy benchmarking, latency optimization, infrastructure orchestration, and integration across our product suite. This is a critical leadership role with direct influence over product velocity, enterprise client outcomes, and future platform scalability. Key ResponsibilitiesVoice-to-Text (ASR) Architecture Lead the design and optimization of large-scale automatic speech recognition (ASR) pipelines using open-source and commercial frameworks (e.g., WhisperX, Deepgram, AWS Transcribe) Enhance speaker diarization, custom vocabulary accuracy, and latency performance for real-time streaming scenarios Build fallback ASR workflows for offline and batch mode processing Implement multilingual and domain-specific tuning, especially for Indian and GCC languages Natural Language Processing and Conversation Analysis Build NLP models for conversation segmentation, intent detection, tone/sentiment analysis, and call scoring Implement multilingual support (Hindi, Arabic, Tamil, etc.) with fallback strategies for mixed-language and dialectal inputs Develop robust algorithms for real-time classification of sales behaviors (e.g., probing, pitching, objection handling) Train and fine-tune transformer-based models (e.g., BERT, RoBERTa, DeBERTa) and sentence embedding models for text analytics GenAI and LLM Integration Design modular GenAI pipelines for nudging, summarization, and response generation using tools like LangChain, LlamaIndex, and OpenAI APIs Implement retrieval-augmented generation (RAG) architectures for contextual, accurate, and hallucination-resistant outputs Build prompt orchestration frameworks that support real-time sales coaching across channels Ensure safety, reliability, and performance of LLM-driven outputs across use cases Infrastructure and Deployment Lead the development of scalable, secure, and low-latency AI services deployed via FastAPI, TorchServe, or similar frameworks Oversee model versioning, monitoring, and retraining workflows using MLflow, DVC, or other MLOps tools Build hybrid inference systems for batch, real-time, and edge scenarios depending on product usage Optimize inference pipelines for GPU/CPU balance, resource scheduling, and runtime efficiency Team Leadership and Cross-functional Collaboration Recruit, manage, and mentor a team of machine learning engineers and research scientists Collaborate closely with Product, Engineering, and Customer Success to translate product requirements into AI features Own AI roadmap planning, sprint delivery, and KPI measurement Serve as the subject-matter expert for AI-related client discussions, sales demos, and enterprise implementation roadmaps Required Qualifications 8+ years of experience in AI/ML with a minimum of 3 years in voice AI, NLP, or conversational platforms Proven experience delivering production-grade ASR or NLP systems at scale Deep familiarity with Python, PyTorch, HuggingFace, FastAPI, and containerized environments (Docker/Kubernetes) Expertise in fine-tuning LLMs and building multi-language, multi-modal intelligence stacks Demonstrated experience with tools such as WhisperX, Deepgram, Azure Speech, LangChain, MLflow, or Triton Inference Server Experience deploying real-time or near real-time inference models at enterprise scale Strong architectural thinking with the ability to design modular, reusable, and scalable ML services Track record of building and leading high-performing ML teams Preferred Skills Background in telecom, contact center AI, conversational analytics, or field sales optimization Familiarity with GPU deployment, model quantization, and inference optimization Experience with low-resource languages and multilingual data augmentation Understanding of sales enablement workflows and domain-specific ontology development Experience integrating AI models into customer-facing SaaS dashboards and APIs Success Metrics Transcription accuracy improvement by ≥15% across core languages within 6 months End-to-end voice-to-nudge latency reduced below 5 seconds GenAI assistant adoption across 70%+ of eligible conversations AI-driven call scoring rolled out across 100% of Tier 1 clients within 9 months Model deployment velocity (dev to prod) reduced by ≥40% through tooling and process improvements Culture at Darwix AI At Darwix AI, we operate at the intersection of engineering velocity and product clarity. We move fast, prioritize outcomes over optics, and expect leaders to drive hands-on impact. You will work directly with the founding team and senior leaders across engineering, product, and GTM functions. Expect ownership, direct communication, and a culture that values builders who scale systems, people, and strategy. Compensation and Benefits Competitive fixed compensation Performance-based bonuses and growth-linked incentives ESOP eligibility for leadership candidates Access to GPU/compute credits and model experimentation infrastructure Comprehensive medical insurance and wellness programs Dedicated learning and development budget for technical and leadership upskilling MacBook Pro, premium workstation, and access to industry tooling licenses Career Progression 12-month roadmap: Build and stabilize AI platform across all product lines 18–24-month horizon: Elevate to VP of AI or Chief AI Officer as platform scale increases globally Future leadership role in enabling new verticals (e.g., healthcare, finance, logistics) with domain-specific GenAI solutions How to Apply Send the following to careers@darwix.ai : Updated CV (PDF format) A short statement (200 words max) on: “How would you design a multilingual voice-to-text pipeline optimized for low-resource Indic languages, with real-time nudge delivery?” Links to any relevant GitHub repos, publications, or deployed projects (optional) Subject Line : “Application – Head of AI & ML Platforms – [Your Name]” Show more Show less

Job Description Job Title : AI Engineer Location : Mohali (Onsite) Shift : UK Shift (12 PM to 10 PM) Experience : 1 to 2 years Qualifications Bachelor's degree in Computer Science, Business, or a related field. Specialization or certification in AI/ML is a plus. Job Role & Responsibilities Develop and optimize predictive models for AI and ML-based features, focusing on enhancing accuracy and latency. Write clean, efficient, reusable, testable, and scalable code with a focus on best coding practices. Analyze business requirements, translate them into software components, and implement feature modifications. Design and implement high-availability, low-latency applications with data protection and security features. Profile applications to ensure optimal performance and identify potential bottlenecks. Continuously work on optimizing NLP-based models, improving both their accuracy and latency for real-world applications. Write unit test cases to ensure code quality and reliability, using appropriate testing frameworks. Continuously optimize and refactor code for improved performance, scalability, and maintainability. Skills & Expertise Strong expertise in building solutions using AI/ML/DL open-source libraries. Advanced Python programming skills. Strong problem-solving and analytical abilities. Ability to write optimized, well-documented code following best coding practices. Proficient in optimizing models for both accuracy and latency, particularly in NLP and machine learning applications. Proficient in optimizing NLP-based models, including techniques for faster inference and reduced computational cost. Familiarity with Generative AI, Large Language Models (LLM), Embeddings, Vectors, RAG (Retrieval-Augmented Generation), and Prompting. Tools & Technologies AI/ML Libraries: TensorFlow, PyTorch, Flair, BERT, DeBERTa, and other latest libraries for text analytics. Frameworks & Platforms: Streamlit, FastAPI. Specialized Tools: Ollama, Vector Databases. Profiling & Testing: Familiarity with tools for profiling applications (e.g., cProfile, Py-Spy) and writing unit tests (e.g., PyTest, UnitTest). Optimization Techniques: Techniques such as model quantization, pruning, distillation, and hardware acceleration. Technical Expertise Minimum of 1 year of hands-on experience in AI/ML/DL projects, focusing on Natural Language Processing (NLP), Named Entity Recognition (NER), and Text Analytics. Strong understanding and practical experience with deep learning techniques, including recommendation engines and advanced AI solutions. Proven experience in optimizing NLP models for accuracy and latency in production environments. Experience with Retrieval-Augmented Generation (RAG) application development and generative AI. Familiarity with Agent Prompting and its applications. Experience in AI applications within the HR domain is highly preferred. Knowledge of Reinforcement Learning is a plus. Certifications or specialization in Artificial Intelligence is highly desirable. Show more Show less

Senior Technical Architect – Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks. What We Offer Joining QX Global Group means becoming part of a creative team where you can personally grow and contribute to our collective goals. We offer competitive salaries, comprehensive benefits, and a supportive environment that values work-life balance. Work Model Location: Ahmedabad Model: WFO Shift Timings: 12:30PM-10PM IST / 1:30PM -11PM IST Show more Show less

We are looking for a skilled AI Engineer to design, build, and optimize advanced AI models and intelligent agents using Azure OpenAI and AI workflow orchestration frameworks . This role involves creating adaptive, secure, and high-performing AI-driven solutions tailored to enhance business workflows through intelligent automation. Key Search Terms: Azure OpenAI, GPT-4, LLMs, AI Workflow Orchestration, AI Agents, LoRA, Quantization, Responsible AI Role Overview: Develop and optimize AI models and specialized agents using Azure OpenAI and AI workflow orchestration frameworks. Create intelligent solutions that integrate with business workflows to deliver personalized business automation. Core Responsibilities: Develop and fine-tune AI models using Azure OpenAI Studio (GPT-4 Turbo, GPT-4o) Design specialized AI agents for business functions Implement model optimization techniques (LoRA, Quantization) Ensure AI components adhere to security standards and ethical AI practices Define KPIs to measure AI agent performance Required Skills: Strong background in AI/ML model development Experience with Azure AI services, particularly Azure OpenAI Understanding of large language models and generative AI Knowledge of data processing techniques for AI applications Experience with model optimization techniques Preferred: Experience with multimodal AI (text, image, voice) Familiarity with low-code/no-code workflow platforms Experience with AI agent architecture Show more Show less

FairAds AI is at the forefront of revolutionizing advertising. We're seeking a highly motivated Machine Learning Engineer / Deep Learning Engineer Intern to join our pioneering team for an immediate start in Mumbai, Maharashtra, India. This is a paid, in-person position . You'll dive deep into developing and deploying, DPDP-compliant ML/DL models for real-time analytics. This is a unique opportunity to work on impactful projects involving Computer Vision, real-time data processing, and privacy-preserving AI. What You'll Help Build & Responsibilities * Develop & Implement ML/DL Models: Design, train, and fine-tune models like YOLO, DeepSORT, and DeepFace for tasks such as impression counting, dwell time analysis, and anonymized demographic analysis. * Advanced Computer Vision Tasks: Apply your OpenCV and CV knowledge for object detection, tracking, pose estimation, and image segmentation on real-world video streams. * Data Preprocessing & Management: Handle raw camera data, including cleaning, annotation, and implementing anonymization techniques (e.g., blurring, feature embeddings) to ensure DPDP Act compliance. Manage datasets using tools like DVC or cloud storage. * Edge Computing & Deployment: Optimize and deploy models on edge devices (e.g., NVIDIA Jetson, Raspberry Pi), managing real-time processing pipelines and considering power/thermal constraints. * Real-Time Analytics: Design streaming data pipelines for video feeds and optimize inference speed (e.g., using TensorRT) to deliver low-latency KPIs. * Privacy by Design: Actively contribute to building privacy-preserving ML pipelines, understanding DPDP Act principles (data minimization, consent, purpose limitation) and implementing secure data handling. * Containerization & CI/CD: Utilize Docker to package and deploy models consistently. Contribute to CI/CD pipelines for automated testing and deployment. Core Technical Skills We're Looking For * Python Programming: Proficiency in Python for ML/DL development, including libraries like PyTorch, TensorFlow, OpenCV, NumPy, Pandas, and Matplotlib. Ability to write modular, reusable code. * Machine Learning & Deep Learning: Strong understanding of supervised/unsupervised learning, neural networks (CNNs), architectures (YOLO, ResNet, ViT), transfer learning, loss functions, optimizers, and regularization. * Computer Vision: Expertise with OpenCV for image/video processing, object detection, tracking, and pose estimation. Experience handling real-time video streams. * Data Preprocessing: Skills in data cleaning, transformation, annotation, and implementing anonymization techniques. Key Domain-Specific & Deployment Skills Needed * Edge Computing: Experience or strong interest in optimizing models (pruning, quantization) for resource-constrained edge hardware (NVIDIA Jetson, Raspberry Pi) and managing real-time edge processing. * Real-Time Analytics: Ability to design streaming data pipelines and optimize for low-latency inference. * Docker & Containerization: Writing Dockerfiles and managing containers for ML model deployment. * Edge Device Deployment: Configuring edge hardware (CUDA, cuDNN), managing cross-compilation, monitoring, and potentially OTA updates. * Version Control & CI/CD (Git, GitHub Actions/Jenkins): Experience with versioning code and models (MLflow, DVC) and automation. * Cloud Integration (Optional but valued): Familiarity with AWS, Azure, or GCP for aggregating anonymized KPIs or model training. API development (Flask/FastAPI) is a plus. Soft Skills for Success * Problem-Solving & Analytical Thinking: Ability to tackle complex challenges in model performance. * Attention to Detail: Meticulous approach to data handling, model accuracy, and compliance requirements. * Pro Vibe Coder: You're someone who can skillfully navigate and debug code, especially code that might have been initially generated or assisted by AI, ensuring its robustness and efficiency. What We Offer * Pioneering Projects: Work on groundbreaking analytics solutions using advanced AI and edge computing. * Hands-on Experience: Gain invaluable experience with the full lifecycle of ML models – from conception to deployment on edge devices. * Mentorship: Learn from experienced professionals in AI, Computer Vision, and privacy-preserving technologies. * Impactful Contribution: Directly contribute to building a more intelligent and compliant ecosystem. Show more Show less

We are looking for a highly skilled Data Scientist with 2-3 years of experience who has worked extensively with Large Language Models (LLMs) and retrieval methods. You will be responsible for building, fine-tuning, and deploying AI models to solve complex NLP challenges. The ideal candidate has hands-on experience in finetuning, optimizing, and implementing LLM-based solutions in real-world applications. Typical work week look like:- Research, fine-tune, and deploy LLMs and other Transformer-based architectures for various NLP tasks. Design and implement custom training pipelines for domain-specific models. Optimize model performance, including prompt engineering, quantization, distillation, and retrieval-augmented generation (RAG). Work with Hugging Face, OpenAI, and other open source foundational model APIs to build scalable solutions. Develop and maintain data pipelines for model training and evaluation. Collaborate with engineering teams to integrate AI models into production systems. Conduct experiments and analyze results to continuously improve model accuracy and efficiency. Stay up to date with cutting-edge advancements in generative AI, LLMs, and NLP. Our ideal candidate should have:- 2+ years of hands-on experience in data science, with a focus on NLP and deep learning. Strong knowledge of Transformer architectures (BERT, GPTs, T5, LLaMA, etc.). Experience in fine-tuning and deploying LLMs using PyTorch, TensorFlow. Proficiency with Hugging Face Transformers, LangChain, OpenAI API, or similar frameworks. Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow). Experience with vector databases (Pinecone, ChromaDB) and retrieval-augmented generation (RAG). Knowledge of cloud platforms (AWS, GCP, Azure) and ML model deployment strategies. Familiarity with MLOps practices, including model monitoring, versioning, and CI/CD for ML. Strong problem-solving skills and ability to work in a fast-paced environment. Preferred Qualifications Experience with multi-modal models (e.g., Whisper, DALL·E). Exposure to LLM inference optimization techniques like quantization, pruning, and knowledge distillation. Experience working on chatbots, conversational AI, or document intelligence solutions. What you can expect from ORI:- Opportunity to work on cutting-edge AI/ML projects. A collaborative, innovation-driven work environment. Passion & happiness in the workplace with great people & open culture with amazing growth opportunities. An ecosystem where leadership is fostered which builds an environment where everyone is free to take necessary actions to learn from real experiences. Freedom to pursue your ideas and tinker If you are passionate about LLMs and pushing the boundaries of AI, we’d love to hear from you! Show more Show less

Job Title: Computer Vision / Deep Learning Engineer Location: Hyderabad, India Experience: Minimum 2 years Employment Type: Full-time Position Overview: We are seeking a Computer Vision / Deep Learning Engineer to join our innovative and fast-paced R&D team. In this role, you will develop cutting-edge vision algorithms for real-time military applications . From early-stage prototyping to embedded system deployment, you will help drive solutions that perform reliably in dynamic and challenging environments. Key Responsibilities: Design and implement deep learning and traditional computer vision algorithms for object detection, segmentation , and multi-object tracking . Translate academic research into scalable, real-world applications for embedded and resource-constrained systems . Develop complete pipelines including data acquisition, model training, evaluation , and deployment . Collaborate with embedded engineers and robotics teams to fine-tune models for field conditions. Participate in agile development practices —sprint planning, code reviews, and integration testing. Continuously optimize models for accuracy, robustness , and low-latency inference on edge devices. Core Technical Skills: Strong programming skills in Python and C++ . Proficient in PyTorch, TensorFlow, OpenCV , and other related libraries. Solid knowledge of image classification, object detection, segmentation, and tracking techniques. Experience with embedded AI deployments on platforms like NVIDIA Jetson, ARM Cortex , etc. Familiarity with performance optimization , quantization , and model pruning for edge inference. Experience with version control (Git) and CI/CD pipelines . Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Electronics, Artificial Intelligence , or a related field. Minimum 2 years of hands-on experience in computer vision and deep learning . Strong understanding of model evaluation metrics , dataset management , and reproducibility best practices . 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

About the Role We are seeking a talented individuals who has recently completed their PhD to join our cutting-edge team. This position is specifically designed for fresh PhD graduates looking to apply their research expertise in a dynamic industry setting. In this role, you'll tackle complex challenges in large language models (LLMs), optical character recognition (OCR), and model scaling. You'll be at the forefront of developing and optimizing AI systems that push the boundaries of what's possible in machine learning. Key Responsibilities Lead research initiatives to improve OCR accuracy across diverse document types and languages Train and fine-tune LLMs using domain-specific data to enhance performance in specialized contexts Develop techniques to scale LLMs efficiently for high-volume production environments Design and implement novel approaches to model optimization and evaluation Collaborate with cross-functional teams to integrate AI solutions into production systems Stay current with the latest research and incorporate state-of-the-art techniques Document methodologies, experiments, and findings for both technical and non-technical audiences Required Qualifications PhD in Computer Science, Machine Learning, AI, or a related field (completed within the last year) Strong understanding of deep learning architectures, particularly transformer-based models Experience with OCR systems and techniques for improving text recognition accuracy Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX) Demonstrated ability to implement and adapt research papers into working code Excellent problem-solving skills with a methodical approach to experimentation Strong communication skills to explain complex technical concepts clearly Preferred Qualifications Research focus during PhD in areas relevant to our work (NLP, computer vision, multimodal learning) Familiarity with distributed training systems for large-scale models Experience with model quantization, pruning, and other efficiency techniques Understanding of evaluation methodologies for assessing model performance Knowledge of MLOps practices and tools for model deployment Publications at top-tier ML conferences (NeurIPS, ICML, ACL, CVPR, etc.) What We Offer Ideal transition from academic research to industry application Structured onboarding program designed specifically for recent PhD graduates Opportunity to work on frontier AI models with real-world impact Access to significant computing resources for ambitious research Collaborative environment with other top AI researchers and engineers Flexible work arrangements and competitive compensation Support for continued professional development and conference attendance Clear path for growth into senior technical or leadership roles Who we are: FourKites® is , the leader in AI-driven supply chain transformation for global enterprises and pioneer of real-time visibility, turns supply chain data into automated action. FourKites’ Intelligent Control Tower™ breaks down enterprise silos by creating a real-time digital twin of orders, shipments, inventory and assets. This comprehensive view, combined with AI-powered digital workers, enables companies to prevent disruptions, automate routine tasks, and optimize performance across As the leader in AI-driven supply chain transformation, FourKites pioneered the Intelligent Control Tower™ powered by the world’s largest real-time visibility network. Our platform creates comprehensive digital twins of your supply chain with AI-powered digital workers to automate resolution, improve collaboration and drive outcomes across all stakeholders. Unlike traditional control towers, we enable true real-time execution and intelligent fulfillment, transforming both your supply and customer (edited) Benefits Medical benefits start on first day of employment 36 PTO days( Sick, Casual and Earned) , 5 recharge days, 2 volunteer days Home Office setups and Technology reimbursement Lifestyle & Family benefits Annual Swags/ Festive Swags Ongoing learning & development opportunities ( Professional development program, Toast Master club etc.) Show more Show less

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Systems Engineering General Summary As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Systems Engineer, you will research, design, develop, simulate, and/or validate systems-level software, hardware, architecture, algorithms, and solutions that enables the development of cutting-edge technology. Qualcomm Systems Engineers collaborate across functional teams to meet and exceed system-level requirements and standards. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Systems Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Systems Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Systems Engineering or related work experience. Principal Engineer – Machine Learning We are looking for a Principal AI/ML Engineer with expertise in model inference , optimization , debugging , and hardware acceleration . This role will focus on building efficient AI inference systems, debugging deep learning models, optimizing AI workloads for low latency, and accelerating deployment across diverse hardware platforms. In addition to hands-on engineering, this role involves cutting-edge research in efficient deep learning, model compression, quantization, and AI hardware-aware optimization techniques . You will explore and implement state-of-the-art AI acceleration methods while collaborating with researchers, industry experts, and open-source communities to push the boundaries of AI performance. This is an exciting opportunity for someone passionate about both applied AI development and AI research , with a strong focus on real-world deployment, model interpretability, and high-performance inference . Education & Experience 20+ years of experience in AI/ML development, with at least 5 years in model inference, optimization, debugging, and Python-based AI deployment. Master’s or Ph.D. in Computer Science, Machine Learning, AI Leadership & Collaboration Lead a team of AI engineers in Python-based AI inference development. Collaborate with ML researchers, software engineers, and DevOps teams to deploy optimized AI solutions. Define and enforce best practices for debugging and optimizing AI models Key Responsibilities Model Optimization & Quantization Optimize deep learning models using quantization (INT8, INT4, mixed precision etc), pruning, and knowledge distillation. Implement Post-Training Quantization (PTQ) and Quantization-Aware Training (QAT) for deployment. Familiarity with TensorRT, ONNX Runtime, OpenVINO, TVM AI Hardware Acceleration & Deployment Optimize AI workloads for Qualcomm Hexagon DSP, GPUs (CUDA, Tensor Cores), TPUs, NPUs, FPGAs, Habana Gaudi, Apple Neural Engine. Leverage Python APIs for hardware-specific acceleration, including cuDNN, XLA, MLIR. Benchmark models on AI hardware architectures and debug performance issues AI Research & Innovation Conduct state-of-the-art research on AI inference efficiency, model compression, low-bit precision, sparse computing, and algorithmic acceleration. Explore new deep learning architectures (Sparse Transformers, Mixture of Experts, Flash Attention) for better inference performance. Contribute to open-source AI projects and publish findings in top-tier ML conferences (NeurIPS, ICML, CVPR). Collaborate with hardware vendors and AI research teams to optimize deep learning models for next-gen AI accelerators. Details Of Expertise Experience optimizing LLMs, LVMs, LMMs for inference Experience with deep learning frameworks: TensorFlow, PyTorch, JAX, ONNX. Advanced skills in model quantization, pruning, and compression. Proficiency in CUDA programming and Python GPU acceleration using cuPy, Numba, and TensorRT. Hands-on experience with ML inference runtimes (TensorRT, TVM, ONNX Runtime, OpenVINO) Experience working with RunTimes Delegates (TFLite, ONNX, Qualcomm) Strong expertise in Python programming, writing optimized and scalable AI code. Experience with debugging AI models, including examining computation graphs using Netron Viewer, TensorBoard, and ONNX Runtime Debugger. Strong debugging skills using profiling tools (PyTorch Profiler, TensorFlow Profiler, cProfile, Nsight Systems, perf, Py-Spy). Expertise in cloud-based AI inference (AWS Inferentia, Azure ML, GCP AI Platform, Habana Gaudi). Knowledge of hardware-aware optimizations (oneDNN, XLA, cuDNN, ROCm, MLIR, SparseML). Contributions to open-source community Publications in International forums / conferences / journals 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. 3072372 Show more Show less

Job Title: AI Researcher – Large Language Models (LLMs) Workplace Type: Work from Office @ Hyderabad Location: Hyderabad, Telangana, India Job Type: Full-Time About Us: We are a well-funded stealth-mode AI startup on a mission to redefine the boundaries of artificial intelligence. Our team is working on next-generation large language models (LLMs) and AI systems that empower businesses with state-of-the-art solutions. Our projects focus on: Training and Fine-Tuning Large Language Models (LLMs) Pioneering AI-Powered Solutions Advancing the Future of AI Technology If you're driven to work at the cutting edge of AI research and love tackling complex problems, this is the opportunity for you! About the Role: We are seeking an AI Researcher with a passion for developing and fine-tuning large language models (LLMs). In this on-site role based in Hyderabad, you’ll contribute to the core AI team, working on groundbreaking projects in natural language processing and generative AI. This role is perfect for someone with 2+ year of hands-on experience who is eager to make a big impact in a fast-paced, innovative environment. Key Responsibilities: Develop, fine-tune, and optimize large language models (LLMs) for various applications. Conduct research on cutting-edge methods in NLP, transformers, and generative AI. Design and implement training pipelines using frameworks like PyTorch or TensorFlow . Work on data preprocessing and augmentation to enhance model performance. Evaluate models using advanced metrics and iterate to improve accuracy, efficiency, and scalability. Collaborate with cross-functional teams to deploy models in production environments. Experiment with and implement state-of-the-art techniques such as LoRA , quantization , or knowledge distillation for efficient model fine-tuning. Stay updated with the latest research papers and advancements in the field of AI and NLP. What We’re Looking For: Education & Experience: A Bachelor’s, Master’s, or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related field. 2+ year of hands-on experience in training and fine-tuning large-scale NLP models or related AI research. Technical Skills: Frameworks : Expertise in deep learning frameworks like PyTorch or TensorFlow . LLM Experience : Hands-on experience with models like GPT, BERT, T5 , or similar transformer-based architectures. Data Handling : Strong skills in preparing, cleaning, and processing large text datasets. Optimization Techniques : Familiarity with fine-tuning methods such as LoRA, Prompt Tuning , or Adapter Training . Evaluation : Knowledge of advanced metrics for NLP tasks (e.g., BLEU, ROUGE, perplexity). Programming : Proficiency in Python and relevant libraries (e.g., Hugging Face Transformers, NumPy, Pandas). Distributed Training : Exposure to multi-GPU training or distributed frameworks is a plus. Bonus Skills: Familiarity with model deployment using frameworks like ONNX , FastAPI , or Docker . Knowledge of efficient model compression techniques (e.g., quantization or pruning). Research contributions (publications, open-source projects) in the field of AI or NLP. Soft Skills: Strong analytical and problem-solving abilities. Excellent communication skills to articulate technical concepts effectively. A collaborative mindset with the ability to thrive in a fast-paced, innovative team. What We Offer: Opportunity to work on cutting-edge AI projects and shape the future of LLMs. A competitive salary and benefits package. A dynamic, research-driven work environment that encourages creativity and innovation. Ready to Build the Future of AI? If you’re passionate about AI research and eager to work on groundbreaking projects, we’d love to hear from you! Show more Show less

ob Title: AI Full stack Developer – GenAI & NLP Location: Pune, India (Hybrid) Work Mode: Remote Experience Required: 2+ Years (Relevant AI/ML with GenAI & NLP) Salary: Up to ₹15 LPA (CTC) Employment Type: Full-time Department: AI Research & Development Role Overview We are looking for a passionate AI Developer with strong hands-on experience in Generative AI and Natural Language Processing (NLP) to help build intelligent and scalable solutions. In this role, you will design and deploy advanced AI models for tasks such as language generation, summarization, chatbot development, document analysis, and more. You’ll work with cutting-edge LLMs (Large Language Models) and contribute to impactful AI initiatives. Key Responsibilities Design, fine-tune, and deploy NLP and GenAI models using LLMs like GPT, BERT, LLaMA, or similar. Build applications for tasks like text generation, question-answering, summarization, sentiment analysis, and semantic search. Integrate language models into production systems using RESTful APIs or cloud services. Evaluate and optimize models for accuracy, latency, and cost. Collaborate with product and engineering teams to implement intelligent user-facing features. Preprocess and annotate text data, create custom datasets, and manage model pipelines. Stay updated on the latest advancements in generative AI, transformer models, and NLP frameworks. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field. Minimum 2 years of experience in fullstack development and AI/ML development, with recent work in NLP or Generative AI. Hands-on experience with models such as GPT, T5, BERT, or similar transformer-based architectures. Proficient in Python and libraries such as Hugging Face Transformers, spaCy, NLTK, or OpenAI APIs. Hands-on experience in any frontend/ backend technologies for software development. Experience with deploying models using Flask, FastAPI, or similar frameworks. Strong understanding of NLP tasks, embeddings, vector databases (e.g., FAISS, Pinecone), and prompt engineering. Familiarity with MLOps tools and cloud platforms (AWS, Azure, or GCP). Preferred Qualifications Experience with LangChain, RAG (Retrieval-Augmented Generation), or custom LLM fine-tuning. Knowledge of model compression, quantization, or inference optimization. Exposure to ethical AI, model interpretability, and data privacy practices. What We Offer Competitive salary package up to ₹15 LPA. Remote work flexibility with hybrid team collaboration in Pune. Opportunity to work on real-world generative AI and NLP applications. Access to resources for continuous learning and certification support. Inclusive, fast-paced, and innovative work culture. Skills: r,kubernetes,next.js,docker,rag architectures,large language models (llms),gcp,embeddings,large language models,bert,javascript,django,machine learning (ml),cloud,tensorflow,machine learning,openai,artificial intelligence,natural language processing (nlp),vector databases,nltk,ai tools,langchain,fastapi,ml,typescript,react.js,java,deep learning,ai development,aws,flask,natural language processing,gpt,nlp tasks,hugging face,hugging face transformers,mlops tools,azure,generative ai,ai technologies,google cloud,node.js,python,nlp,spacy,mlops,ci/cd,pytorch,computer vision 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

Job Description We are looking for an exceptional Data Scientist with deep expertise in speech technologies, advanced NLP, and LLM fine-tuning to join our cutting-edge AI research team. In this pivotal role, you will be responsible for building and optimizing state-of-the-art machine learning pipelines that drive intelligent audio and language-based products. Your work will directly contribute to the development of next-generation AI solutions that are privacy-focused, high-performance, and built for scale. Key Responsibilities Develop and deploy real-time ASR pipelines, leveraging models like Whisper, wav2vec2, or custom speech models. Design and implement robust intent detection and entity extraction systems, utilizing transcribed speech, keyword spotting, and semantic pattern recognition. Fine-tune LLMs and transformer architectures (BERT, RoBERTa, etc.) for tasks including intent classification, entity recognition, and contextual comprehension. Optimize end-to-end pipelines for mobile and on-device inference, employing tools like TFLite, ONNX, quantization, and pruning to achieve low-latency performance. Collaborate closely with AI product teams and MLOps engineers to ensure seamless deployment, continuous iteration, and performance monitoring. Required Technical Skills Hands-on experience with ASR models (Whisper, wav2vec2, DeepSpeech, Kaldi, Silero), with a focus on fine-tuning for Indian languages and multilingual scenarios. Strong command of NLP techniques such as keyword spotting, sequence labeling, masked token prediction, and rule-based classification. Proven track record in LLM and transformer fine-tuning for NER, intent detection, and domain-specific adaptation. Expertise in speech metadata extraction, feature engineering, and signal enrichment. Proficiency in model optimization methods like quantization-aware training (QAT), pruning, and efficient runtime deployment for edge devices. Excellent Python skills with proficiency in PyTorch or TensorFlow, along with solid experience in NumPy, pandas, and real-time data processing frameworks. Qualifications Bachelors or Masters degree in Computer Science, Electrical Engineering, Data Science, or a related technical field. Academic or industry background in speech processing, ASR, telecom analytics, or applied NLP is highly desirable. Portfolio showcasing real-world speech/NLP projects, open-source contributions, or published research will be a strong advantage. Experience 3 to 6+ years of applied experience in speech AI, NLP for intent detection, or machine learning model development. Proven success in building, deploying, and optimizing ML models for real-time, low-latency environments. Contributions to leading open-source projects like openai/whisper, mozilla/DeepSpeech, or facebook/wav2vec2 are highly valued. (ref:hirist.tech) Show more Show less

ob Title: AI Full stack Developer – GenAI & NLP Location: Pune, India (Hybrid) Work Mode: Remote Experience Required: 2+ Years (Relevant AI/ML with GenAI & NLP) Salary: Up to ₹15 LPA (CTC) Employment Type: Full-time Department: AI Research & Development Role Overview We are looking for a passionate AI Developer with strong hands-on experience in Generative AI and Natural Language Processing (NLP) to help build intelligent and scalable solutions. In this role, you will design and deploy advanced AI models for tasks such as language generation, summarization, chatbot development, document analysis, and more. You’ll work with cutting-edge LLMs (Large Language Models) and contribute to impactful AI initiatives. Key Responsibilities Design, fine-tune, and deploy NLP and GenAI models using LLMs like GPT, BERT, LLaMA, or similar. Build applications for tasks like text generation, question-answering, summarization, sentiment analysis, and semantic search. Integrate language models into production systems using RESTful APIs or cloud services. Evaluate and optimize models for accuracy, latency, and cost. Collaborate with product and engineering teams to implement intelligent user-facing features. Preprocess and annotate text data, create custom datasets, and manage model pipelines. Stay updated on the latest advancements in generative AI, transformer models, and NLP frameworks. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field. Minimum 2 years of experience in fullstack development and AI/ML development, with recent work in NLP or Generative AI. Hands-on experience with models such as GPT, T5, BERT, or similar transformer-based architectures. Proficient in Python and libraries such as Hugging Face Transformers, spaCy, NLTK, or OpenAI APIs. Hands-on experience in any frontend/ backend technologies for software development. Experience with deploying models using Flask, FastAPI, or similar frameworks. Strong understanding of NLP tasks, embeddings, vector databases (e.g., FAISS, Pinecone), and prompt engineering. Familiarity with MLOps tools and cloud platforms (AWS, Azure, or GCP). Preferred Qualifications Experience with LangChain, RAG (Retrieval-Augmented Generation), or custom LLM fine-tuning. Knowledge of model compression, quantization, or inference optimization. Exposure to ethical AI, model interpretability, and data privacy practices. What We Offer Competitive salary package up to ₹15 LPA. Remote work flexibility with hybrid team collaboration in Pune. Opportunity to work on real-world generative AI and NLP applications. Access to resources for continuous learning and certification support. Inclusive, fast-paced, and innovative work culture. Skills: computer vision,next.js,r,mlops,artificial intelligence,nltk,flask,aws,react.js,bert,hugging face,embeddings,google cloud,machine learning,machine learning (ml),natural language processing,hugging face transformers,natural language processing (nlp),ci/cd,nlp,django,python,large language models,pytorch,fastapi,large language models (llms),openai,ai technologies,typescript,ai tools,azure,kubernetes,gcp,llama,mlops tools,gpt,vector databases,javascript,rag architectures,nlp tasks,langchain,openai apis,spacy,docker,ai development,tensorflow,ml,node.js,generative ai,java,cloud,deep learning 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

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

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