Machine Learning Data Engineer

Our client specialises in using advanced algorithms and AI to manage and maximise the value of energy storage. By optimising the timing of battery charging and discharging based on real-time market conditions, customers can participate more effectively in multiple energy markets, enhancing the efficiency and profitability of renewable energy resources. We are now looking for a ML Ops / Data Engineer to join their busy, growing and highly successful team.

ML Ops / Data Engineer

Oxford – Hybrid working from home up to 4 days per week.

£75-80K plus excellent benefits package.

To be successful in this role:

We are looking for someone who is a great fit for the company. We want people who take accountability, build trust and are innovative.

Specific requirements for this role include:

• 5+ years of Python experience
• 3+ years of working in technical teams, building data pipelines, delivering productionised code, building/maintaining live applications, developing tooling and improving backtesting frameworks
• 2+ years of orchestrating machine learning workflows
• Proficiency with Orchestration and IaC in AWS (e.g. Terraform, Kubernetes, RabbitMQ, Airflow), Git, containerisation (Docker), database management (e.g. Postgres, Alembic)
• Fluent in Python and its wider numerical ecosystem (e.g. Pandas, NumPy, Polars, Pydantic)
• Additional desirable but not essential requirements for this role include:
• Relational database design
• Cloud infrastructure experience
• Experience with monitoring frameworks (e.g. Prometheus)
• Experience archiving data to Parquet on S3 and creating tools for API/Grafana queries
• Experience centralising diverse datasets for analytics, visualisation and machine learning
• Familiarity with time-series forecasting and/or optimisation
• Experience with data visualisation and dashboards (e.g. Grafana, Superset)
• Familiarity with machine learning and associated techniques (feature engineering, boosting methods, LightGBM)

Position summary:

Our client is looking for smart, motivated people who share a belief that they can outperform the energy sector dinosaurs, have a positive impact on the planet and have fun doing it together.

Job role and responsibilities:

As a ML Ops / Data Engineer, you will be responsible for:

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

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

Enhance data engineering knowledge:Improve expertise within the software team and ensure their ability to support and collaborate on the data science infrastructure

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

Providing backup/escalation to the tech-on-call team

Communicating effectively across Software and Data Science teams

Benefits:

The business values diversity and their environment is highly supportive, challenging and focused on the consistent delivery of high quality, meaningful work. You will receive a competitive salary, flexible working arrangements and a lot of personal development opportunities.

We encourage you to apply even if you may not meet every requirement in this posting.