Machine Learning Engineer

Roles & Responsibilities:

Bachelor's/Master's degree in Computer Science, AI, ML, Data Science, or related technical

field

4+ years of hands-on AI/ML development experience with production deployments with

a total experience of 7-8 yrs.

Strong programming skills in Python (preferred) & Node.js

Sql & No sql exposure is must.

GenAI/LLM expertise: Experience with transformer models, prompt engineering, and LLM

orchestration frameworks (LangChain, LlamaIndex)

Cloud: Proficient in AWS (Sagemaker, AWS SDK, MCP & Bedrock) , OR GCP (Vertex AI,

ADK, and MCP) for building, integrating, and operationalizing cloud-native AI/ML

solutions.

ML/DL proficiency: Solid understanding of machine learning algorithms, deep learning,

and frameworks (TensorFlow, PyTorch, scikit-learn)

Cloud development: Experience with cloud platforms (AWS or GCP preferred) and

containerization (Docker)

Rapid prototyping skills: Ability to quickly build and iterate on proof-of-concepts Selfdirected

learning: Demonstrated ability to independently explore and master new

technologies

Strong analytical and problem-solving capabilities

Tools & Platforms: Vertex AI, Bedrock, SageMaker, ADK, MCP, LangChain, LlamaIndex,

TensorFlow, PyTorch, Docker, and Kubernetes.

GOOD TO HAVE

Experience with vector databases, embeddings, and semantic search technologies

Knowledge of MLOps practices and AI model lifecycle management

Familiarity with microservices architecture and API development

Experience with AI safety, responsible AI practices, and bias mitigation

Contributions to open-source AI/ML projects or technical publications

Experience with agile development methodologies and cross-functional collaboration

Knowledge of additional programming languages (C#, C++)