Machine Learning Operations Engineer

⚡ Role: SW/MLOps Engineer 🌎 Location: Austin, TX 💰 Compensation: $180,000 - $200,000 💼 Benefits: Flexible working arrangements + Strong personal development opportunities Position Overview This is an opportunity to join one of the leading technology-driven battery optimization and energy trading platforms operating across global power markets. The firm specializes in optimizing battery storage and renewable generation assets through advanced quantitative models, forecasting, and automated trading systems. They are looking for a Machine Learning Operations Engineer to help scale and operationalize the analytical infrastructure powering their trading and optimization platform. The role sits at the intersection of machine learning, distributed systems, forecasting, and automated trading, working closely with quantitative researchers, data scientists, and analytics teams. You’ll play a key role in building scalable ML infrastructure, productionizing trading models, and improving the reliability and performance of critical forecasting and optimization systems. Responsibilities • Operationalize ML and trading algorithms into scalable, production-grade workflows • Build and maintain infrastructure supporting forecasting, optimization, and portfolio analytics • Develop tooling and platforms that enable scalable model deployment and lifecycle management • Improve reliability and performance across automated trading and analytics systems • Define architectural standards and scalable cloud-native tooling strategies • Collaborate closely with quantitative researchers, analytics, and trading teams Qualifications • 3+ years of experience in MLOps, ML Engineering, Data Engineering, or related fields • Strong Python experience across data and ML tooling (Pandas, Polars, NumPy, PySpark, etc.) • Experience deploying ML frameworks such as PyTorch, TensorFlow, or Keras into production environments • Hands-on experience with orchestration and MLOps tooling such as MLFlow, Ray, Airflow, or Prefect • Experience working within AWS or similar cloud environments and containerized systems/Kubernetes • Strong understanding of distributed systems, data pipelines, and scalable ML infrastructure Preferred Experience • Exposure to U.S. Power Markets, energy trading, or forecasting systems • Experience with time-series forecasting and market signal analysis • Familiarity with Kafka, Spark, Flink, Snowflake, Iceberg, or related modern data stack technologies • Understanding of optimization techniques including linear or mixed-integer programming • Interest in quantitative trading systems and energy market analytics 📧 Sounds like you? Please click on the ‘Easy Apply’ button. You can also send your resume directly to piruz.hashempour@storm4.com or message me directly! ⚡ Storm4 is a specialist GreenTech recruitment firm with clients across North America. To discuss open opportunities or career options, please visit our website at www.storm4.com and follow the Storm4 LinkedIn page for the latest jobs and information. Show more Show less