317 Quantization Jobs

🚀 We're Hiring: Senior AI/ML Engineer | Join Our Mission to Build the Future of Intelligent Systems Are you passionate about cutting-edge AI and machine learning? Are you eager to build and deploy Large Language Models, intelligent agents, and transformative AI systems at scale? We’re looking for a " Senior AI/ML Engineer" to join our fast-moving team and make a real impact. 🔍 What You’ll Do: Fine-tune and optimize state-of-the-art models (Transformers, CNNs, RNNs) for real-world use cases Apply quantization and other optimization techniques (INT8, INT4, dynamic quantization) to maximize model performance Build, deploy, and scale intelligent AI agents and multi-agent systems Design APIs and services using FastAPI, Flask, or Django REST, and deploy using Docker/Kubernetes across AWS/GCP/Azure Collaborate on production-grade solutions using PyTorch, TensorFlow, Hugging Face Transformers Leverage vector databases (e.g., Pinecone, Weaviate, Chroma) to power intelligent applications ✅ What We’re Looking For: 3+ years of AI/ML development experience with a proven track record of delivering impactful projects Expertise in fine-tuning and deploying LLMs and deep learning models Deep understanding of modern AI workflows and frameworks (Transformers, Agents, RAG, etc.) Strong Python skills and solid software engineering fundamentals Hands-on experience with production environments, CI/CD, and cloud platforms Proficiency in databases (PostgreSQL + vector DBs) and collaborative Git workflows 🌟 Bonus Points For: Experience with distributed training and large-scale model development Familiarity with retrieval-augmented generation (RAG), prompt engineering, and chain-of-thought reasoning. Background in AI ethics or responsible AI practices Start-up or rapid development experience Bachelor’s or Master’s degree in Computer Science, AI, or a related field 🌐 Why Join Us? Work on high-impact, technically challenging problems Be part of a collaborative, fast-moving, and forward-thinking team Build products that leverage cutting-edge AI to solve real-world challenges Shape the direction of intelligent systems from the ground up \#AIJobs #MachineLearning #DeepLearning #LLMs #MLJobs #TechHiring #StartupJobs #ArtificialIntelligence #FastAPI #HuggingFace #PyTorch #Kubernetes #AIEngineer

Role & Responsibilities 4+ years of experience applying AI to practical uses Develop and train computer vision models for tasks like: Object detection and tracking (YOLO, Faster R-CNN, etc.) Image classification, segmentation, OCR (e.g., PaddleOCR, Tesseract) Face recognition/blurring, anomaly detection, etc. Optimize models for performance on edge devices (e.g., NVIDIA Jetson, OpenVINO, TensorRT). Process and annotate image/video datasets; apply data augmentation techniques. Proficiency in Large Language Models. Strong understanding of statistical analysis and machine learning algorithms. Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Understanding of image processing concepts (thresholding, contour detection, transformations, etc.) Experience in model optimization, quantization, or deploying to edge (Jetson Nano/Xavier, Coral, etc.) Strong programming skills in Python (or C++), with expertise in: Implement and optimize machine learning pipelines and workflows for seamless integration into production systems. Hands-on experience with at least one real-time CV application (e.g., surveillance, retail analytics, industrial inspection, AR/VR). OpenCV, NumPy, PyTorch/TensorFlow Computer vision models like YOLOv5/v8, Mask R-CNN, DeepSORT Engage with multiple teams and contribute on key decisions. Expected to provide solutions to problems that apply across multiple teams. Lead the implementation of large language models in AI applications. Research and apply cutting-edge AI techniques to enhance system performance. Contribute to the development and deployment of AI solutions across various domains Requirements Design, develop, and deploy ML models for: OCR-based text extraction from scanned documents (PDFs, images) Table and line-item detection in invoices, receipts, and forms Named entity recognition (NER) and information classification Evaluate and integrate third-party OCR tools (e.g., Tesseract, Google Vision API, AWS Textract, Azure OCR,PaddleOCR, EasyOCR) Develop pre-processing and post-processing pipelines for noisy image/text data Familiarity with video analytics platforms (e.g., DeepStream, Streamlit-based dashboards). Experience with MLOps tools (MLflow, ONNX, Triton Inference Server). Background in academic CV research or published papers. Knowledge of GPU acceleration, CUDA, or hardware integration (cameras, sensors).

Role & Responsibilities 4+ years of experience applying AI to practical uses Develop and train computer vision models for tasks like: Object detection and tracking (YOLO, Faster R-CNN, etc.) Image classification, segmentation, OCR (e.g., PaddleOCR, Tesseract) Face recognition/blurring, anomaly detection, etc. Optimize models for performance on edge devices (e.g., NVIDIA Jetson, OpenVINO, TensorRT). Process and annotate image/video datasets; apply data augmentation techniques. Proficiency in Large Language Models. Strong understanding of statistical analysis and machine learning algorithms. Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms. Understanding of image processing concepts (thresholding, contour detection, transformations, etc.) Experience in model optimization, quantization, or deploying to edge (Jetson Nano/Xavier, Coral, etc.) Strong programming skills in Python (or C++), with expertise in: Implement and optimize machine learning pipelines and workflows for seamless integration into production systems. Hands-on experience with at least one real-time CV application (e.g., surveillance, retail analytics, industrial inspection, AR/VR). OpenCV, NumPy, PyTorch/TensorFlow Computer vision models like YOLOv5/v8, Mask R-CNN, DeepSORT Engage with multiple teams and contribute on key decisions. Expected to provide solutions to problems that apply across multiple teams. Lead the implementation of large language models in AI applications. Research and apply cutting-edge AI techniques to enhance system performance. Contribute to the development and deployment of AI solutions across various domains Requirements Design, develop, and deploy ML models for: OCR-based text extraction from scanned documents (PDFs, images) Table and line-item detection in invoices, receipts, and forms Named entity recognition (NER) and information classification Evaluate and integrate third-party OCR tools (e.g., Tesseract, Google Vision API, AWS Textract, Azure OCR,PaddleOCR, EasyOCR) Develop pre-processing and post-processing pipelines for noisy image/text data Familiarity with video analytics platforms (e.g., DeepStream, Streamlit-based dashboards). Experience with MLOps tools (MLflow, ONNX, Triton Inference Server). Background in academic CV research or published papers. Knowledge of GPU acceleration, CUDA, or hardware integration (cameras, sensors).

Job Description: We are looking for a Lead Generative AI Engineer with 3–5 years of experience to spearhead development of cutting-edge AI systems involving Large Language Models (LLMs) , Vision-Language Models (VLMs) , and Computer Vision (CV) . You will lead model development, fine-tuning, and optimization for text, image, and multi-modal use cases. This is a hands-on leadership role that requires a deep understanding of transformer architectures, generative model fine-tuning, prompt engineering, and deployment in production environments. Roles and Responsibilities: Lead the design, development, and fine-tuning of LLMs for tasks such as text generation, summarization, classification, Q&A, and dialogue systems. Develop and apply Vision-Language Models (VLMs) for tasks like image captioning, VQA, multi-modal retrieval, and grounding. Work on Computer Vision tasks including image generation, detection, segmentation, and manipulation using SOTA deep learning techniques. Leverage frameworks like Transformers, Diffusion Models, and CLIP to build and fine-tune multi-modal models. Fine-tune open-source LLMs and VLMs (e.g., LLaMA, Mistral, Gemma, Qwen, MiniGPT, Kosmos, etc.) using task-specific or domain-specific datasets. Design data pipelines , model training loops, and evaluation metrics for generative and multi-modal AI tasks. Optimize model performance for inference using techniques like quantization, LoRA, and efficient transformer variants. Collaborate cross-functionally with product, backend, and ML ops teams to ship models into production. Stay current with the latest research and incorporate emerging techniques into product pipelines. Requirements: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. 3–5 years of hands-on experience in building, training, and deploying deep learning models, especially in LLM, VLM , and/or CV domains. Strong proficiency with Python , PyTorch (or TensorFlow), and libraries like Hugging Face Transformers, OpenCV, Datasets, LangChain, etc. Deep understanding of transformer architecture , self-attention mechanisms , tokenization , embedding , and diffusion models . Experience with LoRA , PEFT , RLHF , prompt tuning , and transfer learning techniques. Experience with multi-modal datasets and fine-tuning vision-language models (e.g., BLIP, Flamingo, MiniGPT, Kosmos, etc.). Familiarity with MLOps tools , containerization (Docker), and model deployment workflows (e.g., Triton Inference Server, TorchServe). Strong problem-solving, architectural thinking, and team mentorship skills.

bebo Technologies is a leading complete software solution provider. bebo stands for 'be extension be offshore'. We are a business partner of QASource, inc. USA[www.QASource.com]. We offer outstanding services in the areas of software development, sustenance engineering, quality assurance and product support. bebo is dedicated to provide high-caliber offshore software services and solutions. Our goal is to 'Deliver in time-every time'. For more details visit our website: www.bebotechnologies.com Let's have a 360 tour of our bebo premises by clicking on below link: https://www.youtube.com/watch?v=S1Bgm07dPmMKey Required Skills: Bachelor's or Master’s degree in Computer Science, Data Science, or related field. 7–10 years of industry experience, with at least 5 years in machine learning roles. Advanced proficiency in Python and common ML libraries: TensorFlow, PyTorch, Scikit-learn. Experience with distributed training, model optimization (quantization, pruning), and inference at scale. Hands-on experience with cloud ML platforms: AWS (SageMaker), GCP (Vertex AI), or Azure ML. Familiarity with MLOps tooling: MLflow, TFX, Airflow, or Kubeflow; and data engineering frameworks like Spark, dbt, or Apache Beam. Strong grasp of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay). Excellent problem-solving, communication, and documentation skills.

Position Overview- We are looking for an experienced AI Engineer to design, build, and optimize AI-powered applications, leveraging both traditional machine learning and large language models (LLMs). The ideal candidate will have a strong foundation in LLM fine-tuning, inference optimization, backend development, and MLOps, with the ability to deploy scalable AI systems in production environments. ShyftLabs is a leading data and AI company, helping enterprises unlock value through AI-driven products and solutions. We specialize in data platforms, machine learning models, and AI-powered automation, offering consulting, prototyping, solution delivery, and platform scaling. Our Fortune 500 clients rely on us to transform their data into actionable insights. Key Responsibilities: Design and implement traditional ML and LLM-based systems and applications. Optimize model inference for performance and cost-efficiency. Fine-tune foundation models using methods like LoRA, QLoRA, and adapter layers. Develop and apply prompt engineering strategies including few-shot learning, chain-of-thought, and RAG. Build robust backend infrastructure to support AI-driven applications. Implement and manage MLOps pipelines for full AI lifecycle management. Design systems for continuous monitoring and evaluation of ML and LLM models. Create automated testing frameworks to ensure model quality and performance. Basic Qualifications: Bachelor’s degree in Computer Science, AI, Data Science, or a related field. 4+ years of experience in AI/ML engineering, software development, or data-driven solutions. LLM Expertise Experience with parameter-efficient fine-tuning (LoRA, QLoRA, adapter layers). Understanding of inference optimization techniques: quantization, pruning, caching, and serving. Skilled in prompt engineering and design, including RAG techniques. Familiarity with AI evaluation frameworks and metrics. Experience designing automated evaluation and continuous monitoring systems. Backend Engineering Strong proficiency in Python and frameworks like FastAPI or Flask. Experience building RESTful APIs and real-time systems. Knowledge of vector databases and traditional databases. Hands-on experience with cloud platforms (AWS, GCP, Azure) focusing on ML services. MLOps & Infrastructure Familiarity with model serving tools (vLLM, SGLang, TensorRT). Experience with Docker and Kubernetes for deploying ML workloads. Ability to build monitoring systems for performance tracking and alerting. Experience building evaluation systems using custom metrics and benchmarks. Proficient in CI/CD and automated deployment pipelines. Experience with orchestration tools like Airflow. Hands-on experience with LLM frameworks (Transformers, LangChain, LlamaIndex). Familiarity with LLM-specific monitoring tools and general ML monitoring systems. Experience with distributed training and inference on multi-GPU environments. Knowledge of model compression techniques like distillation and quantization. Experience deploying models for high-throughput, low-latency production use. Research background or strong awareness of the latest developments in LLMs. Tools & Technologies We Use Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Serving: vLLM, TensorRT-LLM, SGlang, OpenAI API Infrastructure: Docker, Kubernetes, AWS, GCP Databases: PostgreSQL, Redis, Vector Databases We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

Humanli.AI is a Startup founded by Alumnus of IIM' Bangalore/ISB Hyderabad & IIM' Calcutta. We are democratizing and extending technology that were accessible & consumed only by MNC’s or Fortune companies to SME and Mid-size firms. We are pioneers in bringing Knowledge Management algorithms & Large Language Models into Conversational BOT framework. Job Title: AI/ML Engineer Location: Jaipur Job Type: Full-time Experience: 0-3 years Job Description: We are looking for an experienced AI/ML & Data Engineer to join our team and contribute to the development and deployment of our AI-based solutions. As an AI/ML & Data Engineer, you will be responsible for designing and implementing data models, algorithms, and pipelines for training and deploying machine learning models. Responsibilities: Design, develop, and fine-tune Generative AI models (e.g., LLMs, GANs, VAEs, Diffusion Models). Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases (FAISS, Pinecone, ChromaDB, Weaviate). Develop and integrate AI Agents for task automation, reasoning, and decision-making. Work on fine-tuning open-source LLMs (e.g., LLaMA, Mistral, Falcon) for specific applications. Optimize and deploy transformer-based architectures for NLP and vision-based tasks. Train models using TensorFlow, PyTorch, Hugging Face Transformers. Work on prompt engineering, instruction tuning, and reinforcement learning (RLHF). Collaborate with data scientists and engineers to integrate models into production systems. Stay updated with the latest advancements in Generative AI, ML, and DL. Optimize models for performance improvements, including quantization, pruning, and low-latency inference techniques. Qualification: B.Tech in Computer Science. Fresher's may apply 0-3 years of experience in data engineering and machine learning. Immediate joiners: Preferred Requirement Experience with data preprocessing, feature engineering, and model evaluation. Understanding of transformers, attention mechanisms, and large-scale training. Hands-on experience with, RAG, LangChain/LangGraph, LlamaIndex, and other agent frameworks. Understanding of prompt tuning, LoRA/QLora, and efficient parameter fine-tuning (PEFT) techniques. Strong knowledge of data modeling, data preprocessing, and feature engineering techniques. Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform. Excellent problem-solving skills and ability to work independently and collaboratively in a team environment. Strong communication skills and ability to explain technical concepts to non-technical stakeholders.

As a Senior AI Engineer with React Native expertise, you will be responsible for developing and integrating AI features using various LLMs such as Norah AI, OpenAI GPT, Google Gemini, and Claude. Your tasks will include creating AI-driven onboarding processes, recommendations, virtual assistants, and news digests. Additionally, you will implement instant voice translation through the Google Translate API, personalized notifications based on user preferences and location, and optimize AI models for mobile platforms like TensorFlow Lite and Core ML to ensure low latency, offline support, and battery efficiency. In the realm of React Native front-end development, you will be tasked with building responsive, cross-platform UI/UX features such as onboarding flows, event booking systems, concierge chat interfaces, and navigation components. You will integrate real-time functionalities like WebSockets, Firebase push notifications, and third-party APIs such as Almosafer, BlackLane, Uber, BLE beacons, and Marcom. Ensuring accessibility, security measures like OAuth and JWT, and cultural alignment for example, understanding Saudi etiquette will also be crucial aspects of your responsibilities. Your role will involve feature implementation across various areas including onboarding and personalization, booking and planning, concierge services and AI assistant functionalities, navigation and real-time capabilities, engagement and security features, as well as admin support for analytics, event monitoring, and emergency alerts. You will be required to test AI accuracy, bias, and mobile performance, optimizing for offline usage, real-time updates, and accessibility. Collaboration with cross-functional teams to align with MoT protocols and documenting AI pipelines and React Native code will be essential parts of your job. To qualify for this position, you should have at least 5 years of experience in AI engineering, with a minimum of 3 years of experience integrating AI into React Native mobile apps for iOS and Android platforms. You should possess expertise in AI/ML frameworks like TensorFlow, PyTorch, and Hugging Face, as well as familiarity with LLMs such as OpenAI and Google Gemini. Proficiency in React Native, JavaScript/TypeScript, Redux, and UI libraries like React Native Elements is required. Strong skills in API integrations, voice APIs like Google Translate, real-time systems, and secure authentication methods are also necessary. Knowledge of mobile AI optimization techniques and navigation technologies is a plus. A Bachelor's or Master's degree in Computer Science, AI/ML, or a related field is preferred for this role. In addition to technical skills, you should have strong problem-solving abilities, collaboration skills, and effective communication with both technical and non-technical stakeholders. This is a full-time position located in person. When applying, please specify your notice period and total experience of 4 years.,

Position title Lead Engineer - AI/ML Description Prospus Consulting Pvt. Ltd. is a fully remote IT consulting company specializing in SaaS solutions. We are looking to hire a highly skilled and experienced Lead AI/ML Engineer to focus on AI-enabling a SaaS application. If you have a passion for innovation and a proven track record in AI/ML software development, we invite you to join our team. Responsibilities Lead the development and integration of AI/ML capabilities into a SaaS application. Design, train, fine-tune, and deploy large language models (LLMs) using advanced embedding techniques. Develop and implement Natural Language Processing (NLP) solutions, including tokenization, attention mechanisms, and sentiment analysis. Perform tasks such as text summarization, semantic search, and supervised/unsupervised learning. Optimize AI/ML models using techniques like quantization, pruning, and distillation. Create and manage searchable vector databases derived from extensive knowledge bases. Build and deploy intelligent chatbots to enhance user experience. Collaborate with cross-functional teams to define project requirements and deliver AI-enabled features. Evaluate model performance using industry-standard metrics and implement improvements as needed. Skills 6+ years of experience in AI/ML software development. Hands-on experience with LLM fine-tuning and embedding techniques. Proficiency in NLP frameworks, tokenization, and attention mechanisms. Demonstrated expertise in sentiment analysis, text summarization, and semantic search. Strong knowledge of supervised and unsupervised learning methodologies. Experience in model distillation and optimization (e.g., quantization, pruning). Hands-on experience with Hugging Face transformers. Proficiency in Python for AI/ML applications. Proven track record of building chatbots and conversational AI systems. Experience creating searchable vector databases from large knowledge bases. Expertise in evaluating model performance and using appropriate metrics. Qualifications Familiarity with AI/ML applications in SaaS platforms. Experience working with remote teams and agile methodologies. Strong problem-solving and analytical skills. Contacts To apply for this position, please complete the mandatory application form linked below. Only applications that include submission of this form will be considered. We appreciate your understanding and look forward to reviewing your application! Submit Your Application Here

Position Overview- We are looking for an experienced AI Engineer to design, build, and optimize AI-powered applications, leveraging both traditional machine learning and large language models (LLMs). The ideal candidate will have a strong foundation in LLM fine-tuning, inference optimization, backend development, and MLOps, with the ability to deploy scalable AI systems in production environments. ShyftLabs is a leading data and AI company, helping enterprises unlock value through AI-driven products and solutions. We specialize in data platforms, machine learning models, and AI-powered automation, offering consulting, prototyping, solution delivery, and platform scaling. Our Fortune 500 clients rely on us to transform their data into actionable insights. Key Responsibilities: Design and implement traditional ML and LLM-based systems and applications Optimize model inference for performance and cost-efficiency Fine-tune foundation models using methods like LoRA, QLoRA, and adapter layers Develop and apply prompt engineering strategies including few-shot learning, chain-of-thought, and RAG Build robust backend infrastructure to support AI-driven applications Implement and manage MLOps pipelines for full AI lifecycle management Design systems for continuous monitoring and evaluation of ML and LLM models Create automated testing frameworks to ensure model quality and performance Basic Qualifications: Bachelor’s degree in Computer Science, AI, Data Science, or a related field 4+ years of experience in AI/ML engineering, software development, or data-driven solutions LLM Expertise Experience with parameter-efficient fine-tuning (LoRA, QLoRA, adapter layers) Understanding of inference optimization techniques: quantization, pruning, caching, and serving Skilled in prompt engineering and design, including RAG techniques Familiarity with AI evaluation frameworks and metrics Experience designing automated evaluation and continuous monitoring systems Backend Engineering Strong proficiency in Python and frameworks like FastAPI or Flask Experience building RESTful APIs and real-time systems Knowledge of vector databases and traditional databases Hands-on experience with cloud platforms (AWS, GCP, Azure) focusing on ML services MLOps & Infrastructure Familiarity with model serving tools (vLLM, SGLang, TensorRT) Experience with Docker and Kubernetes for deploying ML workloads Ability to build monitoring systems for performance tracking and alerting Experience building evaluation systems using custom metrics and benchmarks Proficient in CI/CD and automated deployment pipelines Experience with orchestration tools like Airflow Hands-on experience with LLM frameworks (Transformers, LangChain, LlamaIndex) Familiarity with LLM-specific monitoring tools and general ML monitoring systems Experience with distributed training and inference on multi-GPU environments Knowledge of model compression techniques like distillation and quantization Experience deploying models for high-throughput, low-latency production use Research background or strong awareness of the latest developments in LLMs Tools & Technologies We Use Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Serving: vLLM, TensorRT-LLM, SGlang, OpenAI API Infrastructure: Docker, Kubernetes, AWS, GCP Databases: PostgreSQL, Redis, Vector Databases We are proud to offer a competitive salary alongside a strong healthcare insurance and benefits package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

Job Title: AI & ML Developer (Python) Company: ChicMic Studios Location: Mohali, Punjab (Hybrid Options Available) Job Type: Full-Time | 5 Days Working Experience Required: 5+ Years Immediate Joiners Preferred Job Summary: ChicMic Studios is seeking an experienced and innovative AI/ML Developer with strong expertise in Python-based web development and machine learning. The ideal candidate will have 5+ years of hands-on experience with Django, Flask , and cloud deployment on AWS , along with a solid understanding of transformer architectures , model deployment , and MLOps practices . Key Responsibilities: Develop and maintain robust web applications using Django and Flask Build and manage scalable RESTful APIs using Django Rest Framework (DRF) Deploy, manage, and optimize applications using AWS services : EC2, S3, Lambda, RDS, etc. Design and integrate AI/ML APIs into production systems Build ML models using PyTorch, TensorFlow, Scikit-learn Implement transformer architectures like BERT, GPT for NLP and vision tasks Apply model optimization techniques: quantization, pruning, hyperparameter tuning Deploy models using SageMaker, TorchServe, TensorFlow Serving Ensure high performance and scalability of deployed AI systems Collaborate with cross-functional teams to deliver scalable AI-powered products Follow clean coding practices, conduct code reviews, and stay current with AI/ML advancements Required Skills & Qualifications: Btech/ MCA 5+ years of Python development experience Expertise in Django , Flask , and DRF Solid experience deploying apps and models on AWS Proficiency in PyTorch , TensorFlow , and Scikit-learn Experience with transformer models (BERT, GPT, etc.) Strong knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB) Familiarity with MLOps practices for end-to-end model management Bonus: Basic front-end skills (JavaScript, HTML, CSS) Excellent communication and problem-solving skills Why Join ChicMic Studios? Global exposure across 16+ modern tech stacks High retention culture and innovation-driven environment Opportunity to work on cutting-edge AI/ML and NLP projects EPF, Earned Leaves, Career Growth Support Hybrid/WFH flexibility for exceptional candidates To Apply: Send your resume to: disha.mehta755@chicmicstudios.in Contact: +91 98759 52834 Website: www.chicmicstudios.in Job Type: Full-time Pay: ₹800,000.00 - ₹1,800,000.00 per year Benefits: Flexible schedule Provident Fund Work from home Education: Bachelor's (Required) Experience: Python: 5 years (Required) AI: 2 years (Required) Language: English (Required) Work Location: In person

Job Title: AI & ML Developer (Python) Company: ChicMic Studios Location: Mohali, Punjab (Hybrid Options Available) Job Type: Full-Time | 5 Days Working Experience Required: 5+ Years Immediate Joiners Preferred Job Summary: ChicMic Studios is seeking an experienced and innovative AI/ML Developer with strong expertise in Python-based web development and machine learning. The ideal candidate will have 5+ years of hands-on experience with Django, Flask , and cloud deployment on AWS , along with a solid understanding of transformer architectures , model deployment , and MLOps practices . Key Responsibilities: Develop and maintain robust web applications using Django and Flask Build and manage scalable RESTful APIs using Django Rest Framework (DRF) Deploy, manage, and optimize applications using AWS services : EC2, S3, Lambda, RDS, etc. Design and integrate AI/ML APIs into production systems Build ML models using PyTorch, TensorFlow, Scikit-learn Implement transformer architectures like BERT, GPT for NLP and vision tasks Apply model optimization techniques: quantization, pruning, hyperparameter tuning Deploy models using SageMaker, TorchServe, TensorFlow Serving Ensure high performance and scalability of deployed AI systems Collaborate with cross-functional teams to deliver scalable AI-powered products Follow clean coding practices, conduct code reviews, and stay current with AI/ML advancements Required Skills & Qualifications: Btech/ MCA 5+ years of Python development experience Expertise in Django , Flask , and DRF Solid experience deploying apps and models on AWS Proficiency in PyTorch , TensorFlow , and Scikit-learn Experience with transformer models (BERT, GPT, etc.) Strong knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB) Familiarity with MLOps practices for end-to-end model management Bonus: Basic front-end skills (JavaScript, HTML, CSS) Excellent communication and problem-solving skills Why Join ChicMic Studios? Global exposure across 16+ modern tech stacks High retention culture and innovation-driven environment Opportunity to work on cutting-edge AI/ML and NLP projects EPF, Earned Leaves, Career Growth Support Hybrid/WFH flexibility for exceptional candidates To Apply: Send your resume to: disha.mehta755@chicmicstudios.in Contact: +91 98759 52834 Website: www.chicmicstudios.in Job Type: Full-time Pay: ₹800,000.00 - ₹1,800,000.00 per year Benefits: Flexible schedule Provident Fund Work from home Education: Bachelor's (Required) Experience: Python: 5 years (Required) AI: 2 years (Required) Language: English (Required) Work Location: In person

Job Description: 7–10 years of industry experience, with at least 5 years in machine learning roles. Advanced proficiency in Python and common ML libraries: TensorFlow, PyTorch, Scikit-learn. Experience with distributed training, model optimization (quantization, pruning), and inference at scale. Hands-on experience with cloud ML platforms: AWS (SageMaker), GCP (Vertex AI), or Azure ML. Familiarity with MLOps tooling: MLflow, TFX, Airflow, or Kubeflow; and data engineering frameworks like Spark, dbt, or Apache Beam. Strong grasp of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay). Excellent problem-solving, communication, and documentation skills.

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

As a Senior Machine Learning Engineer at TrueFan, you will be at the forefront of AI-driven content generation, leveraging cutting-edge generative models to build next-generation products. Your mission will be to redefine the content generation space through advanced AI technologies, including deep generative models, text-to-video, image-to-video, and lipsync generation. Your responsibilities will include designing, developing, and deploying cutting-edge models for end-to-end content generation. This will involve working on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media. You will research and develop state-of-the-art generative models such as Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. Additionally, you will build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models. Furthermore, you will be responsible for developing advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Your role will also involve implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques. Collaboration with software engineers to deploy models efficiently on cloud-based architectures will be a key aspect of your work. To qualify for this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with 3+ years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks such as PyTorch is essential. Strong problem-solving abilities, a research-oriented mindset, and familiarity with generative adversarial techniques are also required. Preferred qualifications include experience with transformers and vision-language models, background in text-to-video generation and lipsync generation, expertise in cloud-based AI pipelines, and contributions to open-source projects or published research in AI-generated content. If you are passionate about AI-driven content generation and have a strong background in generative AI, this is the perfect opportunity for you to drive research and development in AI-generated content and real-time media synthesis at TrueFan.,

About Us QuillBot is an AI-powered writing platform on a mission to reimagine writing. QuillBot provides over 50 million monthly active uses students, professionals, and educators with free online writing and research tools to help them become more effective, productive, and confident. The QuillBot team was built on the idea that learning how to write and use that knowledge is empowering. They want to automate the more time-consuming parts of writing so that users can focus on their craft. Whether you're writing essays, social media posts, or emails, QuillBot has your back. It has an array of productivity-enhancing tools that are already changing the way the world writes. In the recent chain of events, we were also acquired by CourseHero, which is a 15-year-old Ed-Tech unicorn based out of California, now known as Learneo. Overview QuillBot is looking for a hands-on MLOps Manager to lead and scale our AI Engineering & MLOps function. This role blends deep technical execution (60%) with team and cross-functional collaboration (40%), and is ideal for someone who thrives in a dual IC + strategic lead position. You'll work closely with Research, Platform, Infra, and Product teams — not only to deploy models reliably, but also to accelerate experimentation, training, and iteration cycles. From infra support for large-scale model training to scaling low-latency inference systems in production, you'll be at the heart of how AI ships at QuillBot. Responsibilities Own the full ML lifecycle: from training infra and experiment tracking to deployment, observability, and optimization. Work closely with researchers to remove friction in training, evaluation, and finetuning workflows. Guide and mentor a small, mature team of engineers (3–4), while still contributing as an individual contributor. Drive performance optimization (latency, throughput, cost efficiency), model packaging, and runtime reliability. Build robust systems for CI/CD, versioning, rollback, A/B testing, monitoring, and alerting. Ensure scalable, secure, and compliant AI infrastructure across training and inference environments. Collaborate with cloud and AI providers (e.g., AWS, GCP, OpenAI) as needed to integrate tooling, optimize costs, and unlock platform capabilities. Contribute to other GenAI and cross-functional AI initiatives as needed, beyond core MLOps responsibilities. Contribute to architectural decisions, roadmap planning, and documentation of our AI engineering stack. Champion automation, DevOps/MLOps best practices, and technical excellence across the ML lifecycle. Qualifications 5+ years of strong experience in MLOps, ML/AI Engineering. Solid understanding of ML/DL fundamentals and applied experience in model deployment and training infra. Proficient with cloud-native ML tooling (e.g., GCP, Vertex AI, Kubernetes). Comfortable working on both training-side infra and inference-side systems. Good to have experience with model optimization techniques (e.g., quantization, distillation, FasterTransformer, TensorRT-LLM). Proven ability to lead complex technical projects end-to-end with minimal oversight. Strong collaboration and communication skills — able to work cross-functionally and drive technical clarity. Ownership mindset — comfortable making decisions and guiding others in ambiguous problem spaces." Benefits & Perks Competitive salary, stock options & annual bonus Medical coverage Life and accidental insurance Vacation & leaves of absence (menstrual, flexible, special, and more!) Developmental opportunities through education & developmental reimbursements & professional workshops Maternity & parental leave Hybrid & remote model with flexible working hours On-site & remote company events throughout the year Tech & WFH stipends & new hire allowances Employee referral program Premium access to QuillBot Benefits and benefit amounts differ by region. A comprehensive list applicable to your region will be provided in your interview process. Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. We strongly encourage you to apply if you're interested: we'd love to learn how you can amplify our team with your unique experience! This role is eligible for hire in India. We are a virtual-first company and have employees dispersed throughout the United States, Canada, India and the Netherlands. We have a market-based pay structure that varies by location. The base pay for this position is dependent on multiple factors, including candidate experience and expertise, and may vary from the amounts listed. You may also be eligible to participate in our bonus program and may be offered benefits, and other types of compensation. #QuillBot Equal Employment Opportunity Statement (EEO) We are an equal opportunity employer and value diversity and inclusion within our company. We will consider all qualified applicants without regard to race, religion, color, national origin, sex, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or ability status. We will ensure that individuals who are differently abled are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment as provided to other applicants or employees. Please contact us to request accommodation.

About Us QuillBot is an AI-powered writing platform on a mission to reimagine writing. QuillBot provides over 50 million monthly active uses students, professionals, and educators with free online writing and research tools to help them become more effective, productive, and confident. The QuillBot team was built on the idea that learning how to write and use that knowledge is empowering. They want to automate the more time-consuming parts of writing so that users can focus on their craft. Whether you're writing essays, social media posts, or emails, QuillBot has your back. It has an array of productivity-enhancing tools that are already changing the way the world writes. In the recent chain of events, we were also acquired by CourseHero, which is a 15-year-old Ed-Tech unicorn based out of California, now known as Learneo. Overview QuillBot is looking for a hands-on MLOps Manager to lead and scale our AI Engineering & MLOps function. This role blends deep technical execution (60%) with team and cross-functional collaboration (40%), and is ideal for someone who thrives in a dual IC + strategic lead position. You'll work closely with Research, Platform, Infra, and Product teams — not only to deploy models reliably, but also to accelerate experimentation, training, and iteration cycles. From infra support for large-scale model training to scaling low-latency inference systems in production, you'll be at the heart of how AI ships at QuillBot. Responsibilities Own the full ML lifecycle: from training infra and experiment tracking to deployment, observability, and optimization. Work closely with researchers to remove friction in training, evaluation, and finetuning workflows. Guide and mentor a small, mature team of engineers (3–4), while still contributing as an individual contributor. Drive performance optimization (latency, throughput, cost efficiency), model packaging, and runtime reliability. Build robust systems for CI/CD, versioning, rollback, A/B testing, monitoring, and alerting. Ensure scalable, secure, and compliant AI infrastructure across training and inference environments. Collaborate with cloud and AI providers (e.g., AWS, GCP, OpenAI) as needed to integrate tooling, optimize costs, and unlock platform capabilities. Contribute to other GenAI and cross-functional AI initiatives as needed, beyond core MLOps responsibilities. Contribute to architectural decisions, roadmap planning, and documentation of our AI engineering stack. Champion automation, DevOps/MLOps best practices, and technical excellence across the ML lifecycle. Qualifications 5+ years of strong experience in MLOps, ML/AI Engineering. Solid understanding of ML/DL fundamentals and applied experience in model deployment and training infra. Proficient with cloud-native ML tooling (e.g., GCP, Vertex AI, Kubernetes). Comfortable working on both training-side infra and inference-side systems. Good to have experience with model optimization techniques (e.g., quantization, distillation, FasterTransformer, TensorRT-LLM). Proven ability to lead complex technical projects end-to-end with minimal oversight. Strong collaboration and communication skills — able to work cross-functionally and drive technical clarity. Ownership mindset — comfortable making decisions and guiding others in ambiguous problem spaces." Benefits & Perks Competitive salary, stock options & annual bonus Medical coverage Life and accidental insurance Vacation & leaves of absence (menstrual, flexible, special, and more!) Developmental opportunities through education & developmental reimbursements & professional workshops Maternity & parental leave Hybrid & remote model with flexible working hours On-site & remote company events throughout the year Tech & WFH stipends & new hire allowances Employee referral program Premium access to QuillBot Benefits and benefit amounts differ by region. A comprehensive list applicable to your region will be provided in your interview process. Research shows that candidates from underrepresented backgrounds often don't apply for roles if they don't meet all the criteria. We strongly encourage you to apply if you're interested: we'd love to learn how you can amplify our team with your unique experience! This role is eligible for hire in India. We are a virtual-first company and have employees dispersed throughout the United States, Canada, India and the Netherlands. We have a market-based pay structure that varies by location. The base pay for this position is dependent on multiple factors, including candidate experience and expertise, and may vary from the amounts listed. You may also be eligible to participate in our bonus program and may be offered benefits, and other types of compensation. #Learneo Equal Employment Opportunity Statement (EEO) We are an equal opportunity employer and value diversity and inclusion within our company. We will consider all qualified applicants without regard to race, religion, color, national origin, sex, gender identity, gender expression, sexual orientation, age, marital status, veteran status, or ability status. We will ensure that individuals who are differently abled are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment as provided to other applicants or employees. Please contact us to request accommodation. About Learneo Learneo is a platform of builder-driven businesses, including Course Hero, CliffsNotes, LitCharts, Quillbot, Symbolab, and Scribbr, all united around a shared mission of supercharging productivity and learning for everyone. We attract and scale high growth businesses built and run by visionary entrepreneurs. Each team innovates independently but has a unique opportunity to collaborate, experiment, and grow together, and they are supported by centralized corporate operations functions, including HR, Finance and Legal.

Company Size Large-scale / Global Experience Required 3 - 5 years Working Days 6 days/week Office Location Viman Nagar, Pune Role & Responsibilities Agentic AI Development: Design and develop multi-agent conversational frameworks with adaptive decision-making capabilities. Integrate goal-oriented reasoning and memory components into agents using transformer-based architectures. Build negotiation-capable bots with real-time context adaptation and recursive feedback processing. Generative AI & Model Optimization: Fine-t une LLMs/SLMs using proprietary and domain-specific datasets (NBFC, Financial Services, etc.). Apply distillation and quantization for efficient deployment on edge devices. Benchmark LLM/SLM performance on server vs. edge environments for real-time use cases. Speech And Conversational Intelligence: Implement contextual dialogue flows using speech inputs with emotion and intent tracking. Evaluate and deploy advanced Speech-to-Speech (S2S) models for naturalistic voice responses. Work on real-time speaker diarization and multi-turn, multi-party conversation tracking. Voice Biometrics & AI Security: Train and evaluate voice biometric models for secure identity verification. Implement anti-spoofing layers to detect deepfakes, replay attacks, and signal tampering. Ensure compliance with voice data privacy and ethical AI guidelines. Self-Learning & Autonomous Adaptation: Develop frameworks for agents to self-correct and adapt using feedback loops without full retraining. Enable low-footprint learning systems on-device to support personalization on the edge. Ideal Candidate Educational Qualifications: Bachelors/Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience Required: 35 years of experience, with a mix of core software development and AI/ML model engineering. Proven hands-on work with Conversational AI, Generative AI, or Multi-Agent Systems. Technical Proficiency: Strong programming in Python, TensorFlow/PyTorch, and model APIs (Hugging Face, LangChain, OpenAI, etc.). Expertise in STT, TTS, S2S, speaker diarization, and speech emotion recognition. LLM fine-tuning, model optimization (quantization, distillation), RAG pipelines. Understanding of agentic frameworks, cognitive architectures, or belief-desire-intention (BDI) models. Familiarity with Edge AI deployment, low-latency model serving, and privacy-compliant data pipelines. Desirable: Exposure to agent-based simulation, reinforcement learning, or behavioralmodeling. Publications, patents, or open-source contributions in conversational AI or GenAI systems. Perks, Benefits and Work Culture Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of Indias most diversified Non-banking financial companies, and among Asias top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations were present in India. Skills: edge ai deployment,adaptation,speech emotion recognition,llm fine-tuning,tensorflow,models,intelligence,model optimization,speech,speech-to-speech,data,openai,hugging face,llm,optimization,agents,langchain,pytorch,python Show more Show less

JD for Generative AI Specialist JD Junior / Senior Generative AI Specialist Year of experience Junior / Senior 4-6 Years or 6- 8 years Shift : 11AM - 8PM Location : Chennai. Mode : Work From Office Role -The Generative AI specialist should be building GenAI LLM model driven solution using State of the Art Models like ( OpenAI, Gemini, Claude) , Opensource Models ( llama, Mistral). Should have expertise in fine tuning and training models . Should have implemented projects with expertise on Agents, Tools and RAG solutions. Hands on expertise in integrating LLMs with VectorDB like chromadb, faiss, pinecone is required. Expertise in PEFT, Quantization of models is required. Experience in Tensorflow, Pytorch, Python, Hugging Face, Transformers is must. Expert in data preparation, analysis and hands one expertise in Deep Learning model development is preferred. Additional expertise in deploying models in AWS is desired but optional. Skills OpenAI, Gemini, LangChain, Transformers, Hugging Face, Python, Pytorch, Tensorflow, Vectordb( chromadb, faiss, pinecone) Project experience Atleast 1-2 live implementation of Generative AI driven solution implementation. Extensive experience in implementing chatbots, knowledge search and in NLP . Good expertise in implementing Machine learning and deep learning solutions for atleast 2 years. 4th Floor, Techno Park, 10, Rajiv Gandhi Salai, Customs Colony, Sakthi Nagar, Thoraipakkam, Chennai 600097 Skills: rag,nlp,aws,vectordb (chromadb, faiss, pinecone),claude,agents,tensorflow,langchain,chatbots,hugging face,analysis,transformers,python,chromadb,gemini,openai,deep learning,faiss,llms,opensource models,pytorch,genai llm,peft,machine learning,llama,vectordb,mistral,pinecone

Job purpose: Design, develop, and deploy end-to-end AI/ML systems, focusing on large language models (LLMs), prompt engineering, and scalable system architecture. Leverage technologies such as Java/Node.js/NET to build robust, high-performance solutions that integrate with enterprise systems. Who You Are: Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. PhD is a plus. 10+ years of experience in AI/ML development, with at least 2 years working on LLMs or NLP. Proven expertise in end-to-end system design and deployment of production-grade AI systems. Hands-on experience with Java/Node.js/.NET for backend development. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers). Key Responsibilities: 1. Model Development & Training: Design, train, and fine-tune large language models (LLMs) for tasks such as natural language understanding, generation, and classification. Implement and optimize machine learning algorithms using frameworks like TensorFlow, PyTorch, or Hugging Face. 2. Prompt Engineering: Craft high-quality prompts to maximize LLM performance for specific use cases, including chatbots, text summarization, and question-answering systems. Experiment with prompt tuning and few-shot learning techniques to improve model accuracy and efficiency. 3. End-to-End System Design: Architect scalable, secure, and fault-tolerant AI/ML systems, integrating LLMs with backend services and APIs. Develop microservices-based architectures using Java/Node.js/.NET for seamless integration with enterprise applications. Design and implement data pipelines for preprocessing, feature engineering, and model inference. 4. Integration & Deployment: Deploy ML models and LLMs to production environments using containerization (Docker, Kubernetes) and cloud platforms (AWS/Azure/GCP). Build RESTful or GraphQL APIs to expose AI capabilities to front-end or third-party applications. 5. Performance Optimization: Optimize LLMs for latency, throughput, and resource efficiency using techniques like quantization, pruning, and model distillation. Monitor and improve system performance through logging, metrics, and A/B testing. 6. Collaboration & Leadership: Work closely with data scientists, software engineers, and product managers to align AI solutions with business objectives. Mentor junior engineers and contribute to best practices for AI/ML development. What will excite us: Strong understanding of LLM architectures and prompt engineering techniques. Experience with backend development using Java/Node.js (Express)/.NET Core. Familiarity with cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes, CI/CD). Knowledge of database systems (SQL, NoSQL) and data pipeline tools (Apache Kafka, Airflow). Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced, collaborative environment. What will excite you: Lead AI innovation in a fast-growing, technology-driven organization. Work on cutting-edge AI solutions, including LLMs, autonomous AI agents, and Generative AI applications. Engage with top-tier enterprise clients and drive AI transformation at scale. Location: Ahmedabad

About Zupee We are the biggest online gaming company with largest market share in the Indian gaming sector’s largest segment — Casual & Boardgame. We make skill-based games that spark joy in the everyday lives of people by engaging, entertaining, and enabling earning while at play. In the three plus years of existence, Zupee has been on a mission to improve people’s lives by boosting their learning ability, skills, and cognitive aptitude through scientifically designed gaming experiences. Zupee presents a timeout from the stressful environments we live in today and sparks joy in the lives of people through its games. Zupee invests in people and bets on creating excellent user experiences to drive phenomenal growth. We have been running profitable at EBT level since Q3, 2020 while closing Series B funding at $102 million, at a valuation of $600 million. Zupee is all set to transform from a fast-growing startup to a firm contender for the biggest gaming studio in India.. ABOUT THE JOB Role: Senior Machine Learning Engineer Reports to: Manager- Data Scientist Location: Gurgaon Experience: 3-6 Years Role & Responsibilities 1) Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. 2) Collaborate with ML teams to optimize models for inference performance, latency, and resource utilization. 3) Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. 4) Implement techniques such as model quantization, pruning, knowledge distillation, or hardware-specific optimizations (e.g., TensorRT, ONNX). 5) Architect, design, and develop reusable tools, libraries, and infrastructure to accelerate ML deployment and performance analysis for the broader organization. 6) Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. 7) Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. 8) Optimization of the queries and pipelines. Modernization of the applications whenever required. Must - Have Skills: 1) MlOps 2) Python 3) AWS 4) Bash 5) Kubernetes Desired Skills 1) Sagemaker 2) Triton 3) Nvidia 4) GPU 5) Model Optimization

As the AI Solutions Architect, you will be responsible for designing and implementing AI/ML solutions to advance the ZL Platform. Your role involves collaborating with stakeholders to identify business needs, proposing technical solutions, and overseeing the implementation of the chosen solutions. You will partner with Engineering, Product, and Sales teams to secure design wins at customers, enabling the development and growth of ZL product features through customer feedback and PoC evaluations. Additionally, you will be accountable for the success, quality, and timely delivery of AI/ Machine Learning components. Acting as a problem solver, you will address organizational and process challenges by leveraging your technical expertise to bridge gaps, streamline operations, and facilitate the smooth execution of partnership initiatives. It is crucial to stay updated on AI and Data Engineering trends to enhance team performance and product quality. In terms of qualitative expectations, you are expected to foster a culture of innovation, continuous improvement, and excellence in software development. You should take ownership of problems, acquire necessary knowledge, and demonstrate the ability to work efficiently in an environment with loosely defined tasks and competing priorities. Collaboration with various teams within the organization, including Engineering/Research, Sales, Product, and Marketing, is essential. Effective verbal and written communication skills, as well as technical presentation abilities, are key requirements. A self-starter mindset with a passion for growth, enthusiasm for continuous learning, and the ability to share findings across the team are highly valued qualities. The ideal candidate should have experience working in AI/ML for over 10 years, preferably with vector databases, and possess a PhD or master's degree in computer science, Artificial Intelligence, or related disciplines. Knowledge of libraries such as PyTorch and transformers, quantization, model deployment, and fine-tuning LLM using PyTorch is preferred for this role.,

As a Senior Machine Learning Engineer, you will have the exciting opportunity to be involved in designing, developing, and deploying cutting-edge models for end-to-end content generation. This includes working on AI-driven image/video generation, lip syncing, and multimodal AI systems. You will be at the forefront of the latest advancements in deep generative modeling, striving to create highly realistic and controllable AI-generated media. Your responsibilities will encompass researching and developing state-of-the-art generative models like Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. You will focus on building and optimizing AI pipelines for high-fidelity image/video generation and lip syncing. Additionally, you will be tasked with developing advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. Implementing and optimizing models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques will also be part of your role. Collaboration with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure) will be crucial. Staying updated with the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality will be an essential aspect of the role. Furthermore, designing and conducting experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, as well as refining model architectures will be expected. Active participation in code reviews, improving model efficiency, and documenting research findings to enhance team knowledge-sharing and product development will also be part of your responsibilities. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. You should have a minimum of 3 years of experience working with deep generative models, such as Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks like PyTorch is essential. Expertise in multi-modal AI, text-to-image, and image-to-video generation, as well as audio to lip sync, is required. A strong understanding of machine learning principles and statistical methods is necessary. It would be beneficial to have experience in real-time inference optimization, cloud deployment, and distributed training. Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements are qualities that would be valued. Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training will also be beneficial. Preferred qualifications include experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V), a background in text-to-video generation, lip-sync generation, and real-time synthetic media applications, as well as experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques (quantization, pruning, distillation). Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis would be advantageous.,

Company Size Large-scale / Global Experience Required 3 - 5 years Working Days 6 days/week Office Location Viman Nagar, Pune Role & Responsibilities Agentic AI Development: Design and develop multi-agent conversational frameworks with adaptive decision-making capabilities. Integrate goal-oriented reasoning and memory components into agents using transformer-based architectures. Build negotiation-capable bots with real-time context adaptation and recursive feedback processing. Generative AI & Model Optimization: Fine-t une LLMs/SLMs using proprietary and domain-specific datasets (NBFC, Financial Services, etc.). Apply distillation and quantization for efficient deployment on edge devices. Benchmark LLM/SLM performance on server vs. edge environments for real-time use cases. Speech And Conversational Intelligence: Implement contextual dialogue flows using speech inputs with emotion and intent tracking. Evaluate and deploy advanced Speech-to-Speech (S2S) models for naturalistic voice responses. Work on real-time speaker diarization and multi-turn, multi-party conversation tracking. Voice Biometrics & AI Security: Train and evaluate voice biometric models for secure identity verification. Implement anti-spoofing layers to detect deepfakes, replay attacks, and signal tampering. Ensure compliance with voice data privacy and ethical AI guidelines. Self-Learning & Autonomous Adaptation: Develop frameworks for agents to self-correct and adapt using feedback loops without full retraining. Enable low-footprint learning systems on-device to support personalization on the edge. Ideal Candidate Educational Qualifications: Bachelor’s/Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience Required: 3–5 years of experience, with a mix of core software development and AI/ML model engineering. Proven hands-on work with Conversational AI, Generative AI, or Multi-Agent Systems. Technical Proficiency: Strong programming in Python, TensorFlow/PyTorch, and model APIs (Hugging Face, LangChain, OpenAI, etc.). Expertise in STT, TTS, S2S, speaker diarization, and speech emotion recognition. LLM fine-tuning, model optimization (quantization, distillation), RAG pipelines. Understanding of agentic frameworks, cognitive architectures, or belief-desire-intention (BDI) models. Familiarity with Edge AI deployment, low-latency model serving, and privacy-compliant data pipelines. Desirable: Exposure to agent-based simulation, reinforcement learning, or behavioralmodeling. Publications, patents, or open-source contributions in conversational AI or GenAI systems. Perks, Benefits and Work Culture Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of India’s most diversified Non-banking financial companies, and among Asia’s top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations we’re present in India. Skills: edge ai deployment,adaptation,speech emotion recognition,llm fine-tuning,tensorflow,models,intelligence,model optimization,speech,speech-to-speech,data,openai,hugging face,llm,optimization,agents,langchain,pytorch,python

Job Description – AI Developer (Agentic AI Frameworks, Computer Vision & LLMs) Location (Hybrid - Bangalore) About the Role We’re seeking an AI Developer who specializes in agentic AI frameworks —LangChain, LangGraph, CrewAI, or equivalents—and who can take both vision and language models from prototype to production. You will lead the design of multi‑agent systems that coordinate perception (image classification & extraction), reasoning, and action, while owning the end‑to‑end deep‑learning life‑cycle (training, scaling, deployment, and monitoring). Key Responsibilities Scope What You’ll Do Agentic AI Frameworks (Primary Focus) Architect and implement multi‑agent workflows using LangChain, LangGraph, CrewAI, or similar. Design role hierarchies, state graphs, and tool integrations that enable autonomous data processing, decision‑making, and orchestration. Benchmark and optimize agent performance (cost, latency, reliability). Image Classification & Extraction Build and fine‑tune CNN/ViT models for classification, detection, OCR, and structured data extraction. Create scalable data‑ingestion, labeling, and augmentation pipelines. LLM Fine‑Tuning & Retrieval‑Augmented Generation (RAG) Fine‑tune open‑weight LLMs with LoRA/QLoRA, PEFT; perform SFT, DPO, or RLHF as needed. Implement RAG pipelines using vector databases (FAISS, Weaviate, pgvector) and domain‑specific adapters. Deep Learning at Scale Develop reproducible training workflows in PyTorch/TensorFlow with experiment tracking (MLflow, W&B). Serve models via TorchServe/Triton/KServe on Kubernetes, SageMaker, or GCP Vertex AI. MLOps & Production Excellence Build robust APIs/micro‑services (FastAPI, gRPC). Establish CI/CD, monitoring (Prometheus, Grafana), and automated retraining triggers. Optimize inference on CPU/GPU/Edge with ONNX/TensorRT, quantization, and pruning. Collaboration & Mentorship Translate product requirements into scalable AI services. Mentor junior engineers, conduct code and experiment reviews, and evangelize best practices. Minimum Qualifications B.S./M.S. in Computer Science, Electrical Engineering, Applied Math, or related discipline. 5+ years building production ML/DL systems with strong Python & Git . Demonstrable expertise in at least one agentic AI framework (LangChain, LangGraph, CrewAI, or comparable). Proven delivery of computer‑vision models for image classification/extraction. Hands‑on experience fine‑tuning LLMs and deploying RAG solutions. Solid understanding of containerization (Docker) and cloud AI stacks (AWS/Azure). Knowledge of distributed training, GPU acceleration, and performance optimization. ---------------------------------------------------------------------------------------------------------------------------------------------------------- Job Type: Full-time Pay: Up to ₹1,200,000.00 per year Experience: AI, LLM, RAG: 4 years (Preferred) Vector database, Image classification: 4 years (Preferred) containerization (Docker): 3 years (Preferred) ML/DL systems with strong Python & Git: 3 years (Preferred) LangChain, LangGraph, CrewAI: 3 years (Preferred) Location: Bangalore, Karnataka (Preferred) Work Location: In person