Machine Learning Engineer

🚀 Machine Learning Engineer📍 Austin, TX (Hybrid/Remote Considered)💰 $140,000 - $180,000 BaseWe're partnering with a fast-growing energy firm looking to hire a Machine Learning Engineer to join a highly technical platform engineering team supporting traders, analysts, and quantitative researchers.This is not a pure data science role. We're looking for an engineer who enjoys building robust production systems, scaling data and ML infrastructure, and working closely with front-office stakeholders to deliver real business impact.What you'll be doing:Building and maintaining ML and data platforms used for forecasting, optimization, and trading workflowsDesigning scalable cloud-native infrastructure and deployment pipelinesProductionizing quantitative models and analytics toolsDeveloping distributed data and compute systemsWorking directly with traders and business users to deliver reliable solutionsDriving engineering best practices across CI/CD, observability, testing, and automationTech stack includes:Python | AWS | Kubernetes | Docker | Terraform | Airflow | Spark | MLflow | Databricks | Kafka | CI/CDWe're interested in people from backgrounds such as:✔ Machine Learning Engineering✔ MLOps Engineering✔ Platform Engineering✔ Software Engineering (with ML/Data exposure)✔ Quant Development✔ Infrastructure EngineeringIdeal candidates will have strong Python skills, cloud and DevOps experience, and a track record of building production systems. Experience within energy, trading, forecasting, or quantitative environments is beneficial but not essential.If you'd like to learn more, please send me a message or apply directly.They prefer the role to be worked on a hybrid model of 1-2 days a week. Salary offered is $140,000-$180,000.