45 Fine Tuning Jobs

Job Title: Senior AI/ML Engineer (Python) Location: Gurgaon, India Employment Type: Full-time Experience Required: 8+ years About the Role: We are seeking a Senior AI/ML Engineer with deep expertise in building, deploying, and fine-tuning advanced machine learning and deep learning models. This role emphasizes LLMs, Hugging Face ecosystem, and fine-tuning techniques like LoRA (Low-Rank Adaptation) for scalable AI-driven applications. The ideal candidate will be a hands-on expert in AI/ML frameworks, end-to-end pipeline development, and modern MLOps practices, while also mentoring teams and contributing to the companys AI strategy. Key Responsibilities: Architect, design, and deploy advanced AI/ML and deep learning models for NLP, computer vision, and multi-modal use cases. Build end-to-end ML pipelines covering data engineering, preprocessing, model training, evaluation, and deployment. Implement fine-tuning techniques (LoRA, parameter-efficient tuning, transfer learning, etc.) for LLMs and domain-specific tasks. Leverage the Hugging Face ecosystem for model development, training, and deployment. Work extensively with Python and ML/DL frameworks (PyTorch, TensorFlow, scikit-learn). Drive adoption of MLOps best practices (CI/CD for ML, MLflow, Kubeflow, Airflow). Collaborate with cross-functional teams to integrate AI models into production-grade applications. Mentor junior engineers and establish best practices for scalable ML engineering . Research and apply state-of-the-art advancements in LLMs, transformers, generative AI, and fine-tuning . Required Skills & Qualifications: Bachelor’s/Master’s degree in Computer Science, Data Science, AI, or related field . 8+ years of hands-on experience in AI/ML development and deployment . Expert in Python programming and ML/DL frameworks (PyTorch, TensorFlow). Strong understanding of machine learning algorithms, deep learning architectures, transformers, and NLP techniques . Proven experience with Hugging Face Transformers, LoRA, and fine-tuning large language models (LLMs) . Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes). Solid knowledge of data preprocessing, feature engineering, and production model deployment . Preferred Skills: Expertise in parameter-efficient fine-tuning (PEFT) and generative AI workflows. Exposure to big data ecosystems (Spark, Hadoop) for large-scale ML applications. Experience in multi-modal AI systems (text, image, and audio). Strong foundation in statistics, optimization, and applied mathematics . Experience leading teams and defining AI strategy & best practices .

Job Description : Generative AI Developer (1- 4 Years) We are looking for a talented Generative AI Developer with 1- 4 years of experience to join our team and contribute to building next-generation AI-driven applications. The ideal candidate will have strong expertise in Python, AI agents, RAG pipelines, and practical experience across machine learning, deep learning, NLP, and computer vision. You will work on designing, developing, and deploying generative AI systems in production. Role & responsibilities Design, develop, and optimize AI agent workflows, including multi-agent systems and agentic RAG pipelines. Implement and maintain solutions using frameworks such as LangChain, LangGraph, or Autogen. Build, fine-tune, and deploy generative AI models (LLMs) for real-world use cases. Work with both relational (PostgreSQL) and non-relational databases (MongoDB), and manage vector databases (Milvus, Qdrant) for semantic search and retrieval. Develop custom machine learning and deep learning models for NLP and computer vision applications. Apply prompt engineering strategies for LLM applications and perform model fine-tuning for domain-specific tasks. Collaborate with cross-functional teams to integrate AI capabilities into scalable products. Stay updated on the latest research in generative AI, multi-agent frameworks, and applied ML solutions. Strong experience in using AI-native development framework like Cursor. Must-Have Skills Strong proficiency in Python. Solid understanding of AI Agents, Multi-Agent Systems, and Agentic RAG. Hands-on experience with LangChain, LangGraph, or Autogen. Knowledge of PostgreSQL, MongoDB, and vector databases (Milvus, Qdrant). Proven experience in developing and deploying Machine Learning and Deep Learning models. Practical knowledge in Natural Language Processing. Experience with Prompt Engineering and LLM fine-tuning.

Build and optimize GenAI model workflows : Fine-tune, evaluate, and productionize LLMs, integrating them into a modular platform. Develop reusable components for model-as-a-service : Abstract prompt engineering, tuning methods (LoRA, PEFT), and deployment logic into scalable microservices. Collaborate with platform and infra teams : Ensure AI workloads are GPU-efficient, monitorable, and tightly integrated with MLOps and DevSecOps standards. Work on Agentic AI frameworks : Build task-driven autonomous agents that integrate tools, APIs, and reasoning workflows across domains. Experience in ML/DL/GenAI with a Master's in Computer Science, AI, or related field. Expertise in LLMs , Transformer architectures , fine-tuning (LoRA/PEFT) , and production deployment. Strong programming in Python with deep experience in PyTorch , FastAPI , and GenAI frameworks like LangChain . Experience with model lifecycle platforms (e.g., SageMaker, Kubeflow, MLflow). Exposure to LLMOps practices , GPU utilization optimization, and model observability. Experience building Agentic AI workflows using tools like AutoGPT, CrewAI, or custom toolchains. Familiarity with RAG pipelines, vector databases (Pinecone, FAISS), and embedding strategies. Working knowledge of multi-modal models, streaming inferencing, and containerized deployment on Kubernetes. Contributions to open-source AI libraries or publications in GenAI.

Location: Hyderabad, India | Employment Type: Full-Time Experience Level: 4+Years Company: Covasant Contact Person: Ranjith Reddy 9703455109 | ranjith.palle@covasant.cm | linkedin.com/in/ranjith-r-75a766227 Build the Future of AI with Covasant At Covasant , we don't just work with AI we engineer the next era of it. We're hiring mid-level to senior developers and AI leads to help us build next-generation agentic AI systems that are intelligent, collaborative, and scalable. This is your chance to go beyond prompt engineering and shape the architecture of autonomous, multi-agent AI solutions using tools like LangGraph, AutoGen, CrewAI , and more. If youve got the skills and curiosity to work on what the AI world will be talking about next year , we want to hear from you. Your Role Design and develop multi-agent LLM systems using LangGraph, AutoGen, or CrewAI. Build and deploy MCP servers , LLM gateways , and design Agent-to-Agent collaboration flows. Fine-tune language models for verticals like healthcare, manufacturing, or finance. Architect retrieval-augmented generation (RAG) systems with vector stores like FAISS, Pinecone, or Weaviate. Integrate tools like LangSmith , GuardrailsAI , and knowledge graphs to ensure trust, safety, and observability. Collaborate cross-functionally with product, data science, and engineering teams. What You Bring 2+ years in software development, with strong Python skills. Proven expertise in one or more: LangGraph , AutoGen , CrewAI . Deep understanding of Agent-based AI , LLM orchestration , and RAG pipelines . Experience fine-tuning LLMs and applying prompt engineering and domain adaptation . Familiarity with tools like LangSmith , PromptGuard , or Guardrails frameworks. Bonus If You Have Cloud experience (AWS, Azure, GCP) Familiarity with Docker, Kubernetes Exposure to multi-modal models (LLaMA, Mistral, Falcon) Frontend tech: React, Angular, or Vue CI/CD, MLOps, or LLMOps knowledge Important Were currently hiring mid-level, senior, and lead professionals with hands-on experience in AI/ML projects . These openings are not for freshers or professionals with less than 2 years of experience but we are planning something exciting for early-career AI talent soon! Why Join Covasant Work on real-world agentic AI systems ahead of industry trends Collaborative and innovation-first work culture Competitive pay, benefits & performance incentives Hybrid/flexible work setup A chance to lead and influence the next chapter in AI Let’s Connect If this excites you — whether or not you're actively job hunting — don’t miss the chance to explore this game-changing opportunity. Ranjith Reddy – 9703455109 ranjith.palle@covasant.cm Connect with me on LinkedIn – I’d love to stay in touch, even if this isn’t the right time. Apply now or just start a conversation. The future of AI doesn’t wait — and neither should you.

Job Description : Role Overview We are looking for a skilled Generative AI Developer with strong hands-on expertise in designing, fine-tuning, and deploying LLM (Large Language Model)-based solutions. The ideal candidate will combine deep technical knowledge of AI/ML with strong software engineering skills to build scalable, production-ready applications powered by Generative AI. You will work closely with data scientists, ML engineers, and product teams to create innovative solutions across multiple domains. Key Responsibilities Develop and deploy Generative AI applications using LLMs, diffusion models, and other foundation models. Fine-tune pre-trained models (GPT, LLaMA, Falcon, Mistral, etc.) for domain[1]specific business use cases. Implement RAG (Retrieval-Augmented Generation) pipelines with vector databases such as FAISS, Pinecone, Weaviate, or Milvus. Build APIs and microservices to integrate Gen AI solutions into enterprise applications. Optimize model performance for scalability, latency, and cost efficiency. Collaborate with data engineers on ETL/ELT pipelines and preparation of unstructured/semi-structured data. Apply prompt engineering and prompt-tuning techniques for improved model accuracy and contextual responses. Ensure responsible AI usage by applying bias mitigation, compliance, and security best practices. Stay updated with the latest research and trends in Generative AI and applied ML. Required Skills & Experience Education: Bachelors or Masters in Computer Science, Artificial Intelligence, Data Science, or a related field. Programming: Strong expertise in Python and libraries/frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex. Generative AI/LLMs: Hands-on experience in training, fine-tuning, and deploying LLMs (GPT, LLaMA, etc.) and working with embeddings. MLOps/Deployment: Experience with cloud platforms (Azure, AWS, GCP), Docker, Kubernetes, CI/CD pipelines for ML deployment. Vector Databases: Knowledge of FAISS, Pinecone, Weaviate, or Milvus. Data Handling: Experience in data preprocessing, data lakes, and pipelines. Cloud AI Services: Familiarity with Azure OpenAI, AWS Bedrock, GCP Vertex AI or equivalents. Strong understanding of software engineering principles (version control, testing, APIs, Agile). Nice to Have Experience with multimodal AI (text, image, speech). Knowledge of RLHF (Reinforcement Learning with Human Feedback). Contributions to open-source AI/ML projects. Certifications in AI/ML or cloud AI platforms. Soft Skills Strong analytical and problem-solving mindset. Excellent communication and collaboration with cross-functional teams. Ability to adapt quickly to evolving technologies and requirements. Self-driven, detail-oriented, and innovation-focused

Python, Deep Learning, Object Detection, Classification, Segmentation., GPU acceleration (CUDA, cuDNN). Model Optimization (pruning, quantization), deploying models to edge devices. Required Candidate profile willingness to explore and contribute to Generative AI and cloud-based AI solutions, C/C++., AWS Cloud AI/ML tools, exposure to GenAI frameworks like OpenAI, Stable Diffusion

Do you have a passion for pushing the boundaries of innovation and excited about the potential of AI to enhance the human experience Come join Cerence AI, the global leader in AI for transportation, specializing in developing AI and voice-powered companions for various vehicles. With over 500 million cars equipped with Cerence technology, we collaborate with prominent automakers like Volkswagen, Mercedes, Audi, Toyota, and more to create intuitive, integrated experiences for safer, connected, and enjoyable journeys. Our team at Cerence AI is dedicated to advancing AI innovation globally, with headquarters in Burlington, Massachusetts, USA, and 16 other offices across Europe, Asia, and North America. We bring together diverse backgrounds and skills to elevate transportation user experiences. Our culture is customer-centric, collaborative, fast-paced, and fun, providing continuous opportunities for learning and career growth. We are looking for a talented and innovative AI Specialist to join our team, focusing on developing advanced speech recognition technologies for our automotive voice assistant model. The ideal candidate will have a strong background in AI/ML technologies, including experience in Speech & GenAI solutions development, research on emerging technologies, and collaboration with cross-functional teams to enhance product offerings. Your role will involve staying updated on the latest AI and NLP trends, designing software components to integrate LLM capabilities, analyzing data insights, testing and validating models for deployment, collaborating with stakeholders, and sharing knowledge through training sessions to foster innovation. Requirements for this role include a Bachelor's degree in computer science, Data Science, Artificial Intelligence, or related fields, proficiency in programming languages like React and Python, experience with dev-Ops, cloud platforms, release pipelines, and BI solutions. Strong analytical, problem-solving, and communication skills are essential for this position. Join Cerence Inc., the global industry leader in creating unique automotive experiences, and be part of a dynamic team driving innovation in voice and AI technology for cars. This exciting opportunity offers meaningful contributions to a rapidly growing industry, with a focus on equal opportunity and a secure workplace environment. Prospective and current employees are encouraged to follow security protocols, report suspicious activities, respect corporate security procedures, adhere to compliance regulations, maintain a zero-tolerance policy for workplace violence, and demonstrate knowledge of information security and data privacy requirements through internal training programs.,

We are hiring a Machine Learning Engineer with a strong foundation in computer vision, image classification, image processing, and prompt-based generative modeling. In this role, you will focus on building and deploying production-grade ML pipelines that process images at scale, integrate generative models, and power visual AI products. Role & responsibilities Build and optimize ML pipelines for image classification, detection, and segmentation tasks. Design, train, fine-tune, and deploy deep learning models using CNNs, Vision Transformers, and diffusion-based models. Work with image datasets (structured/unstructured), including preprocessing, augmentation, normalization, and enhancement techniques. Implement and integrate prompt-based generative models (e.g., Stable Diffusion, DALL•E, or ControlNet). Collaborate with backend and product teams to deploy real-time or batch inference systems (using Docker, TorchServe, TensorRT, etc.). Optimize model performance for speed, accuracy, and size (quantization, pruning, ONNX conversion, etc.). Ensure robust versioning, reproducibility, and monitoring of models in production. Preferred candidate profile 2-4 years of experience building and deploying ML models in production environments. Strong proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. Hands-on experience with CNNs, ViTs, UNets, or other architectures relevant to image-based tasks. Experience with prompt-based image generation models (e.g., Stable Diffusion, Midjourney APIs, DALL•E, or open-source alternatives). Familiarity with OpenCV, albumentations, or similar libraries for image processing. Ability to train and evaluate models on large datasets with proper tracking (e.g., using MLflow or Weights & Biases). Experience with model optimization tools (ONNX, TensorRT, quantization). Comfortable working with GPU-based environments and optimizing training/inference performance. Nice to Have Experience with ControlNet, LoRA, or DreamBooth for custom generative image tuning. Familiarity with deployment using TorchServe, FastAPI, or Triton Inference Server. Knowledge of cloud infrastructure (e.g., AWS Sagemaker, GCP AI Platform) for scalable training/inference. Basic understanding of CI/CD pipelines for ML (MLOps practices).

Sr. AI/ML Engineer Job Summary: We are seeking Senior AI/ML Engineers with 3 to 6 years of experience in implementing, deploying, and scaling AI/ML solutions. This role involves working with generative AI, machine learning, deep learning, and data science to solve business challenges by designing, building, and maintaining scalable and efficient AI/ML applications. Key Responsibilities: AI: Architect scalable Generative AI and Machine Learning applications using AWS Cloud and other cutting-edge technologies. Extensive experience with LLMs and various prompt engineering techniques. Fine-tune and build custom LLMs. Deep understanding of LLM architecture and internal mechanisms. Experience with Langchain, Langgraph, Langfuse, Crew AI, LLM output evaluations, and agentic workflows. Build RAG (Retrieval-Augmented Generation) pipelines and integrate them with traditional applications. Data Science & Machine Learning: Solve complex data science problems and uncover insights using advanced EDA techniques. Implement automated pipelines for data cleaning, preprocessing, and model re-training. Hands-on experience with model experiment tracking and validation techniques. Deploy, track, and monitor models using AWS SageMaker. Strong knowledge of fundamental machine learning concepts, including supervised and unsupervised learning, deep learning, CNNs, and RNNs. Proficiency in working with databases for efficient data storage and retrieval. Experience with data warehouses and data lakes. Computer Vision: Work on complex computer vision problems, including image classification, object detection, segmentation, and image captioning. Skills & Qualifications: 2-3 years of experience in implementing, deploying, and scaling Generative AI solutions. 3-7 years of experience in NLP, Data Science, Machine Learning, and Computer Vision. Proficiency in Python and ML frameworks such as Langchain, Langfuse, LLAMA Index, Langgraph, Crew AI, and LLM output evaluations. Experience with AWS Bedrock, OpenAI GPT models (GPT-4, GPT-4o, GPT-4o-mini), and LLMs such as Claude, LLaMa, Gemini, and DeepSeek. Experience with vector databases like Pinecone, OpenSearch, FAISS, and Chroma, with a strong understanding of indexing mechanisms. Expertise in forecasting, time series analysis, and predictive analytics. Experience with classification, regression, clustering, and other ML models. Proficiency in SageMaker for model training, evaluation, and deployment. Hands-on experience with ML libraries such as Scikit-learn, XGBoost, LightGBM, and CatBoost. Experience with deep learning frameworks such as PyTorch and TensorFlow. Familiarity with Docker, Uvicorn, FastAPI, and Flask for REST APIs. Proficiency in SQL and NoSQL databases, including PostgreSQL and AWS DynamoDB. Experience with caching technologies such as Redis and Memcached.

6+ Years of prior analytics and data science experience in driving projects involving Advanced Analytics and Data Science Collaborate with cross-functional teams including Engineering and Business to experiment, implement and deploy complex AI and Gen AI capabilities Strong experience in Statistical Modelling and in Machine Learning techniques like Regression, GBM, Decision Trees, Random Forest, K-Means Clustering, Strong exposure in NLP/Text Analytics, SVM, LSTM, Deep Learning, Neural network Experience in deep learning frameworks such as Tensor Flow, Keras or PyTorch In-depth understanding and hands on experience in working with Large Language Models along with exposure in fine tuning open source models for variety of use case Strong exposure in prompt engineering, knowledge of vector database, langchain framework and data embeddings Strong problem-solving skills and the ability to iterate and experiment to optimize AI model behavior. Advanced proficiency in Python. Advanced experience in SQL/Hive will be preferred Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP) is a plus. Power BI/Tableau (preferred) Proven analytical and quantitative skills with an ability to use hard data and metrics to back up assumptions, develop business cases and complete root cause analyses Ability to communicate effectively with diverse clients/stakeholders Ability to manage a team Tier I/II candidates preferred

Experience: 6 to 9 Years Location: Chennai, Hyderabad, Bangalore, Pune, Delhi/NCR Notice Period: Immediate / 15 days / Serving NP (preferred) About the Role As a Data Scientist specializing in Generative AI and NLP , you will be at the forefront of AI innovation. You will design and deploy advanced models, including Large Language Models (LLMs) , to solve complex business problems. Partnering with cross-functional teams, you will build scalable, data-driven solutions that bring AI-driven intelligence and creativity to life across industries. Key Responsibilities Generative AI & NLP Development: Design, develop, and deploy advanced applications using models like GPT, LLaMA, and Mistral, along with NLP frameworks, to address client challenges. Model Customization & Fine-Tuning: Apply LoRA, PEFT, and fine-tuning techniques for LLMs to tailor solutions to business-specific needs. Innovative Problem Solving: Apply advanced AI methodologies to deliver scalable, AI-powered solutions that generate measurable business outcomes. Data-Driven Insights: Analyze large datasets to extract insights, identify trends, and guide decision-making. Cross-Functional Collaboration: Work with Consulting, Engineering, and other teams to integrate AI solutions into client strategies. Client Engagement: Interact with clients to understand requirements, design tailored AI solutions, and demonstrate the business value of Generative AI. What We Expect Generative AI & NLP Expertise: Proven experience in developing and deploying Generative AI and NLP frameworks, with hands-on knowledge of LLM fine-tuning and customization. Hands-On Data Science Experience: 6+ years in data science, with strong ML/NLP model deployment experience. AI Innovation: Strong awareness of the latest GenAI/LLM research and ability to apply it in practical solutions. Problem-Solving Mindset: Excellent analytical and solution-oriented approach. Communication Skills: Ability to simplify complex AI concepts for business stakeholders. Mandatory Skills Programming: Python (hands-on). Core Skills: Generative AI, LLM, RAG, Fine-Tuning, NLP Other: Team handling & Client interaction experience

Build Gen AI applications using LLMs (OpenAI, LLaMA,Falcon) Develop (RAG) pipelines with vector databases such as ChromaDB, Pinecone, LanceDB. Implement & optimize prompt engineering, embeddings, & semantic search Fine-tune and adapt pre-trained LLMs Required Candidate profile Strong programming skills in Python LangChain, Transformers (Hugging Face, BERT, GPT models) Vector databases (Chroma, Pinecone, LanceDB, Weaviate, FAISS) Deep Learning, Neural Networks, NLP technique

Role & responsibilities Excellent knowledge on Sybase ASE, Sybase replication database administration, High Availability, Minor & Major Upgrade, Query Fine-Tuning, Capacity Planning etc. Working experience on Sybase Versions ASE 12.5 up to latest version of Sybase ASE/IQ & REP. Experience in design, build and manage Sybase database server. Excellent experience in setting up/ maintaining cluster, Sybase replication server and HA. Excellent understanding of Warm Standby/MSA and Table/Function level Replication. Experience in disaster recovery solutions design, implementation, and testing. Well-versed with database backup & restoration, file systems and RPO/RTO. Analyse, solve and Fix issues in real-time, providing problem resolution end-to-end either by connecting or in the screen-sharing mode. Experience in preparing technical documentation like HLD, LLD, SOP and Run Book documents. Excellent troubleshooting skill. Excellent communication/interpersonal skill. Preferred candidate profile Looking for Immediate Joiners Experience Required: 5-9 Yrs Notice Period: 0-15 Days Joiners please share your updated cv to: dhanunjaya.p.m@happiestminds.com

About the Role We are looking for a highly skilled and motivated AI ML Engineer with a strong background in LLMs, RAG pipelines, MLOps, and Azure Cloud . The ideal candidate should have deep experience in building and fine-tuning LLMs, deploying ML systems at scale, and integrating AI capabilities into enterprise-grade applications. Key Responsibilities Design and implement RAG (Retrieval-Augmented Generation) pipelines and AI agentic systems using LLM frameworks. Fine-tune LLMs and develop narrow, domain-specific models using industry best practices. Collaborate with data scientists and product teams to deploy ML models in production environments. Build and maintain robust MLOps pipelines using MLFlow , ensuring reproducibility and traceability of experiments. Integrate and deploy solutions using Azure DevOps and related cloud services. Implement secure and scalable authentication flows using Azure AD and GraphAPI . Optimize performance of deployed models with a focus on latency, cost, and maintainability. Document and present architecture, experiment results, and production workflows. Required Skills & Experience Strong foundational knowledge in Computer Science, IT systems, and architecture . Proficient in Python , with solid experience in both Object-Oriented and Functional Programming paradigms . Practical experience with LLMs , including open-source models. Hands-on experience with RAG pipelines and AI agentic frameworks . Expertise in MLOps tooling , especially MLFlow , model versioning, and CI/CD for ML. Solid understanding of model deployment and serving using Docker, Kubernetes, FastAPI, etc. Proven experience working with Azure cloud , including: Azure DevOps for pipelines and release management. Azure GraphAPI for organizational data access. Authentication and security protocols . Good communication skills and ability to work in cross-functional teams.

Build and optimize GenAI model workflows : Fine-tune, evaluate, and productionize LLMs, integrating them into a modular platform. Develop reusable components for model-as-a-service : Abstract prompt engineering, tuning methods (LoRA, PEFT), and deployment logic into scalable microservices. Collaborate with platform and infra teams : Ensure AI workloads are GPU-efficient, monitorable, and tightly integrated with MLOps and DevSecOps standards. Work on Agentic AI frameworks : Build task-driven autonomous agents that integrate tools, APIs, and reasoning workflows across domains. Experience in ML/DL/GenAI with a Master's in Computer Science, AI, or related field. Expertise in LLMs , Transformer architectures , fine-tuning (LoRA/PEFT) , and production deployment. Strong programming in Python with deep experience in PyTorch , FastAPI , and GenAI frameworks like LangChain . Experience with model lifecycle platforms (e.g., SageMaker, Kubeflow, MLflow). Exposure to LLMOps practices , GPU utilization optimization, and model observability. Experience building Agentic AI workflows using tools like AutoGPT, CrewAI, or custom toolchains. Familiarity with RAG pipelines, vector databases (Pinecone, FAISS), and embedding strategies. Working knowledge of multi-modal models, streaming inferencing, and containerized deployment on Kubernetes. Contributions to open-source AI libraries or publications in GenAI.

Job Title: Senior AI/ML Engineer Custom LLM & RAG Implementation Location: Hyderabad(WFO) Experience: 7+ years Notice: Immediate About the Role We are seeking a highly skilled and hands-on Senior AI/ML Engineer with strong expertise in building and deploying custom Large Language Models (LLMs) . The ideal candidate will have demonstrable experience in Retrieval-Augmented Generation (RAG) implementations, fine-tuning foundation models , and solving complex problems across domains using applied machine learning and natural language processing. This role is strategic and technical, requiring a blend of research, solution engineering, MLOps maturity, and domain adaptability. Key Responsibilities LLM Development & Deployment Design, build, and deploy customized LLM pipelines tailored to enterprise use cases. Implement end-to-end LLMOps workflows including model packaging, CI/CD, and monitoring. RAG & Fine-Tuning Implement RAG pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate) and document ingestion frameworks (e.g., LangChain, Haystack). Fine-tune open-source LLMs (e.g., LLaMA, Falcon, Mistral, MPT) on proprietary datasets using frameworks like Hugging Face Transformers and PEFT/LoRA. Solution Engineering Translate business problems into ML/LLM solutions with clear problem framing and data strategy . Collaborate with product, data engineering, and domain teams to prototype and deliver scalable solutions. Cross-Functional AI Applications Apply ML/LLM solutions across multiple verticals such as legal document analysis, customer support automation, compliance, supply chain optimization, or medical NLP. Build domain-agnostic prompt engineering strategies and apply zero-shot/few-shot learning where appropriate. Leadership & Mentorship Mentor junior engineers and contribute to AI/ML best practices . Act as a thought partner in innovation and experimentation within the team and with external stakeholders. Required Skills & Qualifications Bachelors or Masters in Computer Science, AI/ML, Data Science, or related field. 5+ years of hands-on experience in ML/NLP , with a recent focus on LLMs and foundation models. Hands on exposure in Transformers, RAG Implementation, LLM's PyTorch/TensorFlow, Lang Chain, OpenAI APIs, and popular model libraries. Experience deploying ML models to production using FastAPI, Docker, Kubernetes , or cloud-native tools (AWS/GCP/Azure). Familiarity with vector databases , embeddings, and search frameworks. Strong understanding of model evaluation metrics , bias/fairness in ML, and responsible AI practices. Ability to work cross-functionally with business, legal, and engineering teams. Preferred Qualifications Experience with RLHF (Reinforcement Learning from Human Feedback) . Published work in open-source communities or AI research conferences. Familiarity with multi-modal AI , autoML , or agentic workflows is a plus. Prior work in regulated domains (e.g., finance, healthcare, legal). Why Join Us Work on cutting-edge AI/LLM use cases that span industries and functions. Lead mission-critical AI initiatives from ideation to deployment. Be part of a collaborative, innovation-driven team shaping the next generation of enterprise AI solutions. Note: Interested candidates can share cv at sahithi.totharamudi@jteksoftware.in

You will be responsible for managing and creating PowerBi Dashboards, generating Server Utilization Reports regularly, and maintaining server status in the master list. You should have a good understanding of Virtualization/Citrix Environment and Farms. Additionally, you will need to establish priorities, handle multiple assignments concurrently in a fast-paced work environment, and possess knowledge in Ticket Management and Change Management. Your role will involve gathering data, converting it into reports and dashboards, handling Azure and on-prem Brokered VDIs, and managing the Citrix Environment end-to-end. You will be accountable for Capacity Management for Citrix servers, Change Management, and Knowledge Management for Virtualization. Moreover, you will be responsible for generating reports on SCCM and Tanium, as well as installing, configuring, troubleshooting, and supporting XenDesktop 7. Experience in implementing and troubleshooting Citrix NetScaler, XenApp/XenDesktop, and ensuring compliance with Best Practices, Optimization, and Fine Tuning on Citrix Infrastructure is essential. Your duties will include administering applications for User Access using Access Central/Service Now, creating Application Packaging, deploying as per stakeholders" requests, and managing deployment compliance. You will also handle Citrix environment-related requests and ensure Server Utilization reports are generated and shared with respective stakeholders. MetLife, a leading financial services company, is committed to creating a more confident future for its colleagues, customers, communities, and the world. Recognized on Fortune magazine's list of the "World's Most Admired Companies" and Fortune Worlds 25 Best Workplaces, MetLife values purpose and empathy in transforming the financial services industry. If you are passionate about making a positive impact, consider joining MetLife where it's #AllTogetherPossible.,

Handson exp with LLM-based solution experience using OpenAI, Gemini, etc. Must have skills in fine-tuning, RAG, agents, vector DBs (ChromaDB, FAISS, Pinecone), LangChain, Hugging Face, TensorFlow, PyTorch. 1-2 GenAI implementations & 2+ yrs in ML/DL.

Role Overview We're looking for a passionate and experienced AIML Engineering Lead to join our Pune team and spearhead the development of production-grade LLM-based agentic platform. In this role, you'll be instrumental in designing scalable infrastructure for our LLM systems and developing robust frameworks for prompt management. As a key team member, you'll have significant influence on our system architecture and technical direction. Job Location The position will be in-person in Pune, India. Key Responsibilities Architect and implement production-grade LLMOps pipelines Develop and maintain prompt engineering and evaluation systems Establish comprehensive monitoring and observability for ML system performance Drive continuous improvement in prompt accuracy using quantitative and qualitative feedback Lead system architecture decisions and guide technical strategy Implement efficient data processing and integration solutions Ensure code quality through rigorous testing, code reviews, and LLM best practices Required Qualifications B.Tech/B.E. in Computer Science, IT, or related field from a reputed institute 5+ years of software development experience, with 2+ years in MLOps/LLMOps Proven experience implementing CI/CD, MLOps, or LLMOps pipelines Production-level expertise with Azure Cloud, AI, ML, and Data Pipeline services Strong proficiency in Python and experience with FastAPI Solid understanding of ML algorithms and solutions Excellent problem-solving skills and ability to work independently Strong communication skills in English Willingness to work U.S. East Coast hours Desired Skills Advanced degree in Data Science, Machine Learning, or Computer Science Experience in productionizing GenerativeAI systems Expertise in optimizing ML-based systems Familiarity with Bicep, Terraform, or related infrastructure automation tools Advanced proficiency in Azure and Python Why Join MarketEngine.ai? - Be part of a high-growth Silicon-Valley startup revolutionizing SMB marketing technology. - Collaborate with industry leaders in AI/ML and marketing experts. - Competitive salary package (Best in industry) - Flexible work arrangements and a dynamic, intellectually stimulating environment - Opportunity to shape the future of demand generation technology for startups and SMBs

As a GenAI Model Developer, your role will involve building and deploying GenAI Models using techniques such as RAG and Fine Tuning. You will be responsible for developing AI/ML algorithms to analyze large volumes of historical data in order to make predictions and recommendations. Additionally, you will implement and optimize deep learning models for generative tasks like image synthesis and voice applications. Collaboration with software engineers to integrate Generative AI models into production systems will be a key aspect of your role. You should be able to evaluate application cases and the problem-solving potential of AI/ML algorithms, ranking them according to their likelihood of success. This will involve comprehending data through exploration and visualization, as well as identifying discrepancies in data distribution. Working with both structured and unstructured data, you will develop various algorithms based on statistical modeling procedures and build scalable machine learning solutions for production. Leveraging cloud platforms for training and deploying large-scale solutions, with a preference for AWS, will also be part of your responsibilities. You should have a working knowledge of managing the ModelOps framework and understand CI/CD processes for product deployment. Collaborating with data engineers to build data and model pipelines, ensuring accuracy, will be essential. You are expected to take complete ownership of assigned projects and have experience working in Agile environments. Proficiency in tools such as JIRA or equivalent project tracking tools is required to succeed in this role.,

About Company Process9 is Indias leading language technology company, poised for a major growth in the domestic and global geographies, to vie for a global leadership in the language technology space. Process9 is the next Unicorn candidate to watch out for. Language services is a $50 billion global industry, while the language market in India is growing by over 30% year-on-year. Process9 is bringing Multilingual Transformation to Enterprises, to make their Digital Transformation complete and scalable. More than 80% of Indian population is not English savvy whereas over 98% of Internet content in India is in English. The need for local language content in India is growing like wild fire. Process9 intends to meet the language needs of the industry and Govt to capture a large share of this unmet need. Being a B2B and SaaS based software company, we develop middleware application platforms for language localization of websites, mobile apps, enterprise applications, digital transaction journeys, digital documents and much more. We develop the best-in-class Natural Language Processing (NLP) software using AI/ML technologies for translation, language processing and voice applications for Indian and global languages that are used by hundreds of leading enterprises in India and now attracting global users on the Internet and Smartphones. Our goal is to connect with all digital users regardless of their native languages and make localization easy-to-use and commercially viable for e-businesses We were one of the finalists in the TOP35 INNOVATIONS at the CNN-IBN networked India campaign. For more information, please visit our website: https://process9.com/ Position: Sr. Data Scientist (Multilingual AI/ML) Location: Gurgaon, Haryana We are seeking an experienced Data Scientist to spearhead our multilingual AI/ML initiatives, focusing on natural language processing, speech technologies, and domain-specific model development. The ideal candidate will have extensive experience in training and fine-tuning transformer-based models, speech recognition/synthesis systems, and large language models for specialized applications. Job Responsibilities: Development of multilingual transformer models for machine translation (OpenNMT) and TTS/STT systems (Coqui TTS). Fine-tune Whisper models for speech to text Fine-tune LLMs for fintech/other domain. Build Agentic chatbots using LangChain/LlamaIndex. Design synthetic data pipelines and cross-lingual training strategies. Mentor team members and drive model deployment with engineering teams. Desired Profile: 4+ years experience in ML/NLP. Strong Python, PyTorch/TensorFlow, and Hugging Face expertise. Experience with MLOps, Docker/Kubernetes, and cloud platforms (AWS/GCP/Azure). Knowledge of data privacy and compliance requirements, especially in fintech contexts

As an AI Specialist at our company based in Hyderabad, you will be responsible for training and fine-tuning LLMs such as LLaMA and Mistral to cater to company-specific use cases. You will play a vital role in customizing and optimizing model performance for seamless production deployment. Collaboration with internal teams for model integration and data pipelines will be a key aspect of your role. It is imperative that you stay abreast of the latest advancements in GenAI and LLM techniques to contribute effectively. To excel in this role, you must possess hands-on experience with LLMs and fine-tuning techniques. Your expertise in the specifics of vector database indexing will be highly beneficial. We are looking for someone with a robust background in advanced AI/ML techniques and database indexing, particularly in the context of production projects. Familiarity with technologies such as LoRA, QLoRA, RAG, and PEFT is desirable. Additionally, your knowledge of model evaluation, optimization, and GPU training will be crucial for success in this position.,

We are seeking a highly skilled Data Scientist with a passion for AI, machine learning, and deep learning to join our dynamic team. The ideal candidate will have experience in generative models, LLMs, and advanced AI techniques, and will contribute to solving complex business challenges. Job Title: Data Scientist Location: Bengaluru, Gurugram, Mumbai, Coimbatore 2+years Of experience in machine learning, deep learning, or Al research, With a focus on generative models. Experience With generative models such as GANS (Generative Adversarial Networks), VAEs (Variational Autoencoders), and transformer-based models (e.g., GPT-3/4, BERT, DALL.E). Understanding of model fine-tuning, transfer learning, and prompt engineering in the context Of large language models (LLMS). Knowledge of reinforcement learning (RL) and other advanced machine learning techniques applied to generative tasks. Strong programming skills in python and familiarity With relevant libraries and frameworks. Proven experience in document detail extraction and feature engineering. Proficiency in data processing and manipulation techniques. Hands-on experience in building data applications using Streamlit or similar tools. Advanced knowledge in prompt engineering, chain of thought processes, and Al agents. Excellent problem-solving skills and the ability to work effectively in a collaborative environment. Strong communication skills to convey complex technical concepts to non-technical stakeholders.

Job Title: Senior AI/ML Engineer Custom LLM & RAG Implementation Location: On-site Experience: 7+ years Industry: Cross-Domain (Finance, Healthcare, Logistics, Retail, LegalTech, etc.) About the Role We are seeking a highly skilled and hands-on Senior AI/ML Engineer with strong expertise in building and deploying custom Large Language Models (LLMs) . The ideal candidate will have demonstrable experience in Retrieval-Augmented Generation (RAG) implementations, fine-tuning foundation models , and solving complex problems across domains using applied machine learning and natural language processing. This role is strategic and technical, requiring a blend of research, solution engineering, MLOps maturity, and domain adaptability. Key Responsibilities LLM Development & Deployment Design, build, and deploy customized LLM pipelines tailored to enterprise use cases. Implement end-to-end LLMOps workflows including model packaging, CI/CD, and monitoring. RAG & Fine-Tuning Implement RAG pipelines using vector databases (e.g., FAISS, Pinecone, Weaviate) and document ingestion frameworks (e.g., LangChain, Haystack). Fine-tune open-source LLMs (e.g., LLaMA, Falcon, Mistral, MPT) on proprietary datasets using frameworks like Hugging Face Transformers and PEFT/LoRA. Solution Engineering Translate business problems into ML/LLM solutions with clear problem framing and data strategy . Collaborate with product, data engineering, and domain teams to prototype and deliver scalable solutions. Cross-Functional AI Applications Apply ML/LLM solutions across multiple verticals such as legal document analysis, customer support automation, compliance, supply chain optimization, or medical NLP. Build domain-agnostic prompt engineering strategies and apply zero-shot/few-shot learning where appropriate. Leadership & Mentorship Mentor junior engineers and contribute to AI/ML best practices . Act as a thought partner in innovation and experimentation within the team and with external stakeholders. Required Skills & Qualifications Bachelors or Master’s in Computer Science, AI/ML, Data Science, or related field. 5+ years of hands-on experience in ML/NLP , with a recent focus on LLMs and foundation models. Deep knowledge of Hugging Face ecosystem , PyTorch/TensorFlow, LangChain, OpenAI APIs, and popular model libraries. Experience deploying ML models to production using FastAPI, Docker, Kubernetes , or cloud-native tools (AWS/GCP/Azure). Familiarity with vector databases , embeddings, and search frameworks. Strong understanding of model evaluation metrics , bias/fairness in ML, and responsible AI practices. Ability to work cross-functionally with business, legal, and engineering teams. Preferred Qualifications Experience with RLHF (Reinforcement Learning from Human Feedback) . Published work in open-source communities or AI research conferences. Familiarity with multi-modal AI , autoML , or agentic workflows is a plus. Prior work in regulated domains (e.g., finance, healthcare, legal). Why Join Us Work on cutting-edge AI/LLM use cases that span industries and functions. Lead mission-critical AI initiatives from ideation to deployment. Be part of a collaborative, innovation-driven team shaping the next generation of enterprise AI solutions.

Mirafra Technologies is Hiring #GenAIEngineer (#RAG, #LLM, #FineTuning) Are you passionate about Generative AI and cutting-edge technologies? Join We're looking for Gen AI Engineers with 3 to 5 years of experience in: Walk-In Date: Thursday, 3rd July 2025 Time: 11:00 AM 1:00 PM Job Location - #Bangalore and #Hyderabad Venue: Mirafra Technologies 2nd Floor, Akshay Tech Park, Plot No. 72 & 73, Vijayanagar, EPIP Zone, Whitefield, Bengaluru, Karnataka 560066 Contact Person: Vignesh D Requirements: 3 to 5yrs Strong experience with Gen AI frameworks Hands-on with LLM architecture and deployment Familiarity with RAG pipelines and fine-tuning techniques Solid programming skills in Python