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5.0 - 9.0 years
0 Lacs
jaipur, rajasthan
On-site
As a Senior Data Engineer + AI, you will play a crucial role in designing and optimizing distributed data pipelines using PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. Your expertise in PySpark, Apache Spark, and Databricks for batch and streaming data pipelines will be instrumental in contributing to high-impact programs with clients. Your strong SQL skills for data analysis, transformation, and modeling will enable you to drive data-driven decision-making and facilitate rapid insight generation. Your responsibilities will involve supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications, as well as creating and maintaining interactive dashboards and BI reports using tools such as Power BI, Tableau, or Looker. You will collaborate with cross-functional teams, including AI scientists, analysts, and business teams, to ensure the successful delivery of use cases. In this role, you will need to have a solid understanding of data warehouse design, relational databases such as PostgreSQL, Snowflake, SQL Server, as well as data lakehouse architectures. Your familiarity with cloud services for data and AI, such as Azure, AWS, or GCP, will be essential for ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments. Furthermore, your exposure to Generative AI, RAG, embedding models, and vector databases like FAISS, Pinecone, ChromaDB, as well as experience with Agentic AI frameworks such as LangChain, Haystack, CrewAI, will be beneficial. Your knowledge of MLflow, Delta Live Tables, or other Databricks-native AI tools, CI/CD, Git, Docker, and DevOps pipelines will also be advantageous in this role. If you have a background in consulting, enterprise analytics, or AI/ML product development, it will further enhance your ability to excel in this position. Your excellent problem-solving and collaboration skills, coupled with your ability to bridge engineering and business needs, will be key to your success as a Senior Data Engineer + AI.,
Posted 3 weeks ago
4.0 - 6.0 years
6 - 8 Lacs
Chennai
Work from Office
Key Responsibilities: LLM Deployment & Optimization Deploy, fine-tune, and optimize open-source LLMs (e.g., LLaMA, Mistral, CodeS, DeepSeek). Implement quantization (e.g., 4-bit, 8-bit) and pruning for efficient inference on commodity hardware. Build and manage inference APIs (REST/gRPC) for production use. Infrastructure Management Set up and manage on-premise GPU servers and VM-based deployments. Build scalable cloud-based LLM infrastructure using AWS (SageMaker, EC2), Azure ML, or GCP Vertex AI. Ensure cost efficiency by choosing appropriate hardware and job scheduling strategies. MLOps & Reliability Engineering Develop CI/CD pipelines for model training, testing, evaluation, and deployment. Integrate version control for models, data, and hyperparameters. Set up logging, tracing, and monitoring tools (e.g., MLflow, Prometheus, Grafana) for model performance and failure detection. Security, Compliance & Performance Ensure data privacy (FERPA/GDPR) and enforce security best practices across deployments. Apply secure coding standards and implement RBAC, encryption, and network hardening for cloud/on-prem. Cross-functional Integration Work closely with AI solution engineers, backend developers, and product owners to integrate LLM services into the platform. Support performance benchmarking and A/B testing of AI features across modules. Documentation & Internal Enablement Document LLM pipelines, configuration steps, and infrastructure setup in internal playbooks. Create guides and reusable templates for future deployments and models. Key Requirements: Education: Bachelors or Masters in Computer Science, AI/ML, Data Engineering, or related field. Technical Skills: Strong Python experience with ML libraries (e.g., PyTorch, Hugging Face Transformers). Familiar with LangChain, LlamaIndex, or other RAG frameworks. Experience with Docker, Kubernetes, and API gateways (e.g., Kong, NGINX). Working knowledge of vector databases (FAISS, Pinecone, Qdrant). Familiarity with GPU deployment tools (CUDA, Triton Inference Server, HuggingFace Accelerate). Experience: 4+ years in an AI/MLOps role, including experience in LLM fine-tuning and deployment. Hands-on work with model inference in production environments (both cloud and on-prem). Exposure to SaaS and modular product environments is a plus.
Posted 1 month ago
17.0 - 18.0 years
17 - 18 Lacs
Bengaluru, Karnataka, India
On-site
We are looking for an experienced Data Scientist with expertise in Generative AI and Large Language Models (LLMs) to join our innovation team. In this role, you will work at the cutting edge of AI technologies, leveraging LLMs to develop intelligent applications that can generate, analyze, and process text data. You will collaborate with data scientists, machine learning engineers, and product teams to build and deploy state-of-the-art AI solutions that solve complex real-world problems. Programming Python GenAI Technologies understanding evaluation LLM-LMM integration, Optimization, Deployment RAG, Knowledge graphs, transformers AWS Bedrock We re hiring Sr. Data Scientist for one of our Leading MNC to join their growing team. This position is based out in Bangalore. Education: Any Engineering
Posted 1 month ago
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