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Machine Learning Engineer

Machine Learning Engineer

Prana TreePune (division)
16 hours ago
Job description

Job Title : ML Engineer

Location : Chennai / Hyderabad / Pune

Work Mode : Work from Office

Experience : 4–8 Years

About the role :

We are seeking a highly skilled Machine Learning Engineer with strong experience in building, deploying, and optimizing AI / ML systems—especially those leveraging LLMs, NLP, GenAI , and cloud-native services. The ideal candidate will have hands-on expertise with AWS (including Bedrock) , modern vector databases such as BetaDB , and production-grade ML orchestration.

Key Responsibilities :

  • Design, develop, and deploy end-to-end machine learning pipelines on AWS.
  • Build and fine-tune LLM-based applications for tasks such as summarization, generation, semantic search, classification, and agent-based workflows.
  • Implement NLP solutions including text preprocessing, embedding pipelines, retrieval systems, and conversational AI.
  • Utilize AWS Bedrock for model hosting, inference orchestration, prompt engineering, evaluation, and optimization.
  • Manage knowledge bases and vector storage using BetaDB or similar platforms for RAG and generative workflows.
  • Develop GenAI architectures , including prompt workflows, agents, RAG pipelines, and evaluation frameworks.
  • Integrate ML models into production systems using scalable APIs, microservices, and CI / CD pipelines.
  • Work cross-functionally with product, engineering, and data teams to deliver high-impact AI solutions.
  • Ensure system reliability, observability, and performance tuning for real-time and batch inference workloads.

Required skills & experience :

  • 4–8 years of experience as an ML Engineer / AI Engineer / NLP Engineer.
  • Strong expertise in :
  • Python , PyTorch / TensorFlow, LangChain, or related ML frameworks.
  • LLMs (OpenAI, Anthropic, Cohere, or OSS like Llama, Mistral).
  • GenAI architectures (RAG, agents, orchestrators, evaluators).
  • NLP techniques : embeddings, vector search, tokenization, entity extraction, topic modeling, transformers.

    • Hands-on experience with :

  • AWS Cloud Services (SageMaker, Lambda, SQS, DynamoDB, ECS / EKS, API Gateway).
  • AWS Bedrock for model hosting, tuning, and orchestration.
  • BetaDB (or similar vector DBs : Pinecone, Weaviate, Milvus).
  • Strong understanding of ML system design , inference optimization, caching, latency management, and API integration.
  • Experience with MLOps / DevOps tools (Docker, GitHub Actions, Terraform, Kubernetes preferred).
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    Machine Learning Engineer • Pune (division)