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Prana Tree
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Machine Learning Engineer

Machine Learning Engineer

Prana Tree

8 years

0 Lacs

pune maharashtra india

Posted:15 hours ago| Platform:

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Skills Required

learning ml ai aws design summarization preprocessing retrieval model inference orchestration engineering evaluation microservices data reliability tuning pytorch tensorflow openai tokenization extraction sagemaker sqs dynamodb api optimization latency management docker github terraform kubernetes

Work Mode

On-site

Job Type

Full Time

Job Description

Job Title: ML Engineer

Location:

Work Mode:

Experience:

About the role:

Machine Learning Engineer

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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