Machine Learning Engineer

19 hours ago


New Delhi, India Prana Tree Full time

Job Title: ML EngineerLocation: Chennai / Hyderabad / PuneWork Mode: Work from OfficeExperience: 4–8 YearsAbout 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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