Expert AI/ML Data Engineer

2 weeks ago

Salem, Tamil Nadu, India beBeeMachineLearning Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Senior Data Engineer - AI/ML Expert

Job Summary:

As a Senior Data Engineer and AI/ML expert, you will be responsible for developing and optimizing complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability.

Key Responsibilities:

  • Design and implement end-to-end machine learning data pipelines using cloud technologies like AWS and Azure.
  • Collaborate with data science teams to review model-ready datasets and feature documentation, ensuring completeness and accuracy.
  • Perform data discovery and analysis of raw data sources, applying business context to meet model development needs.
  • Comfort with exploratory data exploration and tracking data lineage during inception or root cause analysis.
  • Engage with internal stakeholders to understand business processes and translate requirements into analytical approaches.
  • Write and maintain model monitoring scripts, diagnosing issues and coordinating resolutions based on alerts.
  • Serve as a domain expert in machine learning engineering on cross-functional teams for significant initiatives.
  • Stay updated with the latest advancements in AI/ML and apply them to real-world challenges.

Requirements:

  • Undergraduate degree or equivalent experience; a graduate degree is preferred.
  • Minimum of 8 years of relevant work experience.
  • At least 3 years of hands-on experience designing ETL pipelines using AWS services (e.g., Glue, SageMaker).
  • Proficiency in programming languages, particularly Python (including PySpark, PySQL) and familiarity with machine learning libraries and frameworks.
  • Strong understanding of cloud technologies, including AWS and Azure, and experience with NoSQL databases.
  • Familiarity with Feature Store usage, LLMs, GenAI, RAG, Prompt Engineering, and Model Evaluation.
  • Experience with API design and development is a plus. Docker Kubernetes
  • Solid understanding of software engineering principles, including design patterns, testing, security, and version control.
  • Knowledge of Machine Learning Development Lifecycle (MDLC) best practices and protocols.
  • Understanding of solution architecture for building end-to-end machine learning data pipelines.

Benefits:

  • Opportunity to work with cutting-edge AI/ML technologies.
  • Collaborative and dynamic work environment.
  • Professional growth and development opportunities.

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