MLOps Data Architect

3 weeks ago

Bengaluru, India ICF Full time

We are seeking a highly skilled and motivated MLOps Data Architect with expertise in small language models, Azure Fabric, Data Governance, AI Model Evaluation, and Building AI Agents. The ideal candidate will have a strong background in computer science, software development, and cloud infrastructure. This role involves designing, implementing, and maintaining scalable and secure cloud infrastructure, as well as collaborating with cross-functional teams to drive innovation in AI and machine learning.

Key Responsibilities:

Develop and optimize data pipelines for small language models and AI agents. Ensure data governance and compliance with industry standards. Evaluate AI models and implement best practices for model monitoring and maintenance. Develop and optimize complex data pipelines, applying machine learning engineering principles to enhance efficiency and scalability. Employ experimental methodologies, statistics, and machine learning concepts to create self-running AI systems for predictive modeling. 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. Participate in special projects and additional duties as assigned.

Qualifications:

Undergraduate degree or equivalent experience; a graduate degree is preferred. Minimum of 5 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. 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.

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