Machine Learning Lead

10+ years overall IT experience, including 5+ years in Machine Learning Engineering, MLOps, AI Platform Engineering, or AI Operations leadership

Key Responsibilities

• Design and implement production-grade model deployment architectures.
• Develop CI/CD and CT (Continuous Training) pipelines for AI and ML workloads.
• Automate model packaging, testing, validation, deployment, and rollback processes.
• Enable scalable serving infrastructure for ML and GenAI applications.
• Support batch, real-time, and streaming inference architectures.
• Build and manage enterprise AI platforms on cloud and hybrid environments.
• Implement containerized AI workloads using Docker and Kubernetes.
• Establish scalable GPU-enabled environments for model training and inference.
• Monitor model accuracy, drift, bias, performance, latency, and usage.
• Establish alerting and automated remediation mechanisms.
• Develop AI observability dashboards and operational metrics.
• Lead root cause analysis for AI platform and model performance issues.

4. Data & Feature Management

• Establish data lineage and model traceability mechanisms.
• Define data quality controls and validation standards.
• Govern training, validation, and inference datasets.
• Ensure reproducibility and auditability across AI pipelines.

5. Generative AI Operations

• Operationalize GenAI and LLM-based solutions.
• Build deployment frameworks for RAG, Agentic AI, and LLM applications.

5anage prompt versioning, evaluation frameworks, and model governance.

• Define monitoring controls for LLM performance, hallucination rates, and response quality.
• Support model orchestration frameworks including LangChain, LangGraph, CrewAI, and Vertex AI Agents.

6. Stakeholder Management

• Collaborate with business leaders, AI teams, operations teams, and executive stakeholders.
• Translate business requirements into scalable AI operational solutions.
• Present AI operational status and platform roadmap updates to leadership.
• Manage vendor and cloud provider engagements.

Required Technical Skills

Skill Area

Expected Competency

MLOps Platforms

DevOps & Automation

Jenkins, GitHub Actions, GitLab CI/CD,

Containerization

Infrastructure as Code

Terraform, CloudFormation, Ansible

Programming

Python, SQL

BigQuery, Snowflake, Spark, Airflow

GenAI Platforms

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