MLOPS
Storm4
Levin is the parent company of Storm4
⚡ Role: Machine Learning Ops Engineer
💼 Industry: Energy Storage & Trading
🌎 Location: Austin or Remote Option
💰 Salary: $130,000 – $170,000
This is an amazing opportunity for an MLOps Engineer to join a leading global optimizer of battery storage and renewable energy assets. The company’s aim is to maximize the value of grid-scale battery storage, so they are attractive investments, are deployed at scale and enable the energy transition.
This role will be embedded with the Data Science team to develop their model workflows, provide support and improvements, and manage the flow of data through our system.
You will be responsible for:
- Develop Data Science Code: Implement robust, scalable, and efficient Python code that transforms optimization or machine learning prototypes into production-grade solutions, and maintain/improve models.
- Writing Well-Structured Code: Develop clean, maintainable, well-documented code that adheres to best practices. Mentor and support in the continued improvement of coding practices within the Data Science team.
- Supporting Data Engineering Infrastructure: Contribute to the design, development, implementation, and continuous improvement of our data engineering tools, workflows, processes, and platforms. This includes enhancing the architectural foundations and integrating new data management technologies.
- Model Optimization and Backtesting: Assist in development and maintenance of backtesting and model tuning frameworks.
- Data Quality Management: Continuously enhance data quality across multiple dimensions such as accuracy, availability, performance, and accessibility to ensure a clear understanding of data within the company.
‘Must have’ skills and experience:
- 3+ years of Python experience
- 3+ years of working with data scientist/ML researchers to develop tooling, collaborate on backtesting frameworks, build data pipelines, build/maintain orchestration workflows or productionise code.
- Proficiency with Orchestration and IaC (Airflow, ECS, Kubernetes, Terraform, CloudFormation), Git, Containerization (docker), SQL (Postgres, Snowflake)
- You are fluent in Python and its wider numerical ecosystem (Pandas, NumPy, Scikit-learn, Polars, etc.).
‘Nice to have’ skills and experience:
- Data engineering experience collecting, curating, managing and monitoring large time series data
- Experience with monitoring frameworks (Prometheus)
- Machine learning experience especially time-series forecasting & generative ML problems
- Optimization experience especially linear programming / mixed-integer programming.
- Knowledge of a US ISO power market (especially ERCOT)
- Knowledge of time-series forecasting & generative ML problems
- Understanding of probability and statistics
- Understanding and execution of optimization techniques (e.g. linear programming / mixed-integer programming)
- Proficient with optimization modelling packages and solvers
- Experience with data visualization and dashboard technologies (e.g. plot.ly, Dash, Streamlit)