REQUIREMENTS

• At least 5 years of experience as an ML Engineer, MLOps Engineer, or equivalent.
• Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Proven experience with AWS ML services, including SageMaker, Glue, Lambda, Step Functions, S3, and CloudWatch.
• Familiarity with CI/CD and test automation tools (e.g., PyTest, Unittest, GitHub Actions, CodePipeline).
• Experience with infrastructure-as-code, versioning, and model registries.
• Solid understanding of MLOps practices, testing strategies, and production ML requirements.
• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or related field.

PREFERRED QUALIFICATIONS

• Familiarity with Generative AI, LLM deployment, or RAG pipelines using AWS Bedrock, LangChain, or open-source LLMs.
• Experience with vector databases (e.g., FAISS, OpenSearch), feature stores, and model explainability tools.
• AWS certification (e.g., ML – Specialty, Solutions Architect, or DevOps Engineer) is a plus
  Job Types: Full-time, Permanent

Benefits:

• Health insurance

Experience:

• ML/MLOps Engineer: 5 years (Required)

Please refer the Job description for details