Senior MLOps Engineer — Energy Sector (Hybrid)

Certus Sales Recruitment; Austin (TX); On-site; USD 160,000 - 180,000; Full time

Job description

Senior MLOps Engineer – Energy Sector

Austin, TX – Hybrid

$160–180k + Excellent Benefits

Our client, a leader in energy innovation, is seeking a Senior MLOps Engineer to design, deploy, and scale machine learning infrastructure powering forecasting, optimisation, and real-time decision-making.

This is a pivotal role, bridging data science and production systems to ensure models are fast, reliable, and seamlessly embedded in business-critical operations.

Role Overview

• Productionise ML models – Deploy forecasting & optimisation models into live market environments with high availability.
• Build scalable ML infrastructure – Architect systems for training, testing & serving at scale.
• Automate deployments – Design CI/CD workflows to test, package, and release ML code to production.
• Monitor & maintain performance – Implement monitoring, alerting, and retraining pipelines to keep models accurate.
• Collaborate widely – Work with data scientists, engineers, and ops teams to translate prototypes into production.
• Optimise compute & storage – Manage GPU clusters, distributed training, and cloud resources efficiently.
• Standardise operations – Create best practices, documentation, and tooling for reproducibility.
• Enable real-time insights – Integrate live data from ISOs, weather feeds, and telemetry systems.
• Drive innovation – Research tools to improve deployment speed, resilience, and observability.

About You

• 3+ years’ MLOps experience in production environments.
• Skilled in ML serving frameworks (MLflow, TensorFlow Serving, TorchServe, BentoML).
• Strong Python skills for APIs, preprocessing, and ML integration.
• Hands‑on AWS experience (SageMaker, EKS, S3, Lambda) plus Terraform & Kubernetes.
• Proficient in CI/CD tools (GitHub Actions, GitLab CI, Jenkins).
• Familiar with monitoring tools (Prometheus, Grafana, Evidently).
• Expert in Docker & Kubernetes for ML deployment.
• Energy market knowledge is a plus, not a must.
• Degree in Computer Science, Machine Learning, or related field (advanced degree/certs welcome).

What’s on Offer

• $160–180k base + benefits
• Generous PTO
• Flexible hybrid working (3 days WFH)
• Professional development opportunities
• Medical, dental, and vision coverage

If you are ready to take your career to the next level and make a significant impact, apply now!