Tech Lead - MLOps & Infrastructure

Technical lead for MLOps infrastructure, owning design and implementation of production-grade ML pipelines, infrastructure-as-code automation, and model lifecycle management.

Overall Tech Lead for the project: drives architectural decisions, sets technical standards, and ensures the ML platform is reliable, scalable, and compliant with operational and regulatory requirements (validation and reproducibility standards for HCLS AI).

Architect and implement end-to-end MLOps pipelines: CI/CD for model training, evaluation, approval, deployment with audit trails

Design and deploy infrastructure-as-code using Terraform for all ML platform resources

Build automated training jobs on Amazon SageMaker: hyperparameter tuning, distributed training, spot optimization for life sciences workloads

Implement model performance monitoring: data drift detection, prediction quality tracking, automated retraining triggers

Establish CI/CD for ML artifacts: model versioning, container builds, integration testing, staged rollouts with validation gates

Design model registry and artifact management for governance, reproducibility, and 21 CFR Part 11 compliance

Implement infrastructure monitoring, alerting, and auto-scaling for training and inference workloads

Define and enforce MLOps best practices, coding standards, and architectural patterns

Serve as overall Tech Lead: architecture reviews, mentoring, technical decision-making

Coordinate with customer platform, IT security, and quality teams on networking, security, and compliance

Our Product is Our People: We live by this.

We invest in people who invest in themselves.

Your growth is our growth.

True Servant Leadership: Our CTO leads with a "force multiplier" philosophy.

Management is here to empower you and clear roadblocks, not to micromanage.

We won't ask you to do anything we're not willing to do ourselves.

Flat Organization, Real Impact: Your voice and designs will directly shape our technical roadmap and our clients' success.