Senior MLOps Engineer - Energy Sector

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

Benefits offered by this job

Generous PTO

Flexible hybrid working (3 days WFH)

Medical, dental, and vision coverage

Job summary

Certus Sales Recruitment client in energy technology seeks a Senior MLOps Engineer in Austin, TX, hybrid. You will design, deploy, and scale ML infrastructure powering forecasting, optimisation, and real-time decision-making.

You will productionise models, build scalable ML infrastructure, automate deployments, and monitor performance. Collaborate with data scientists and engineers to translate prototypes into production, while optimising compute, storage, and real-time data integration.

Qualifications

• 3+ years MLOps experience in production environments.
• Strong Python skills for APIs and ML integration.
• Experience with ML serving frameworks (MLflow, TensorFlow Serving, TorchServe, BentoML).
• 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.
• Degree in Computer Science, ML, or related field (advanced degrees welcome).

Responsibilities

• Productionise ML models – Deploy forecasting & optimisation models into live environments.
• 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.
• Collaborate widely – Work with data scientists, engineers, and ops teams to productionize prototypes.
• Optimise compute & storage – Manage GPU clusters, distributed training, and cloud resources.
• Standardise operations – Create best practices, documentation, and tooling for reproducibility.
• Enable real-time insights – Integrate live data from ISOs, weather feeds, and telemetry.
• Drive innovation – Research tools to improve deployment speed, resilience, and observability.

Skills

3+ years MLOps experience

Python

ML serving frameworks

AWS (SageMaker, EKS, S3, Lambda)

Terraform

Kubernetes

CI/CD tooling

Monitoring tools

Docker

Energy market knowledge

Education

Degree in Computer Science or related field

Tools

MLflow

TensorFlow Serving

TorchServe

BentoML

GitHub Actions

GitLab CI

Jenkins

Prometheus

Grafana

Evidently

Docker

Kubernetes

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!