Senior Machine Learning Engineer

Summary

Join the Sympower data team as a Senior Machine Engineer and deliver insightful forecasts and optimisations to stakeholders, leveraging your comprehensive skill set in machine learning and engineering.

Requirements

• Experience with building scalable machine learning models
• Familiar with methods for improving model performance and designing and evaluating metrics that help evaluate the model performance in a business context
• Experience with ELT data pipeline development/big data processing, preferably with Python (Spark)
• A software-engineering mindset, approach and skillset
• Familiar with the Lake House concept for data storage
• Experience with git, CI/CD, testing frameworks, and DevOps
• Experience and affinity with mentoring and coaching other team members, helping them to grow
• Good stakeholder communication and being comfortable presenting or facilitating meetings with different audiences, using the right level of detail
• Experience driving a project from start to end, including planning, task breakdown, discussions with stakeholders and working together with product management
• Challenging and steering the team’s technical and product roadmap
• Fluent in English and other languages are nice to have

Responsibilities

• Take ownership of implementing production-worthy, scalable machine learning models, with a focus on forecasting and optimisation use cases
• Conduct machine learning experiments to demonstrate the value of forecasting and optimisation models to stakeholders
• Develop batch and streaming machine learning pipelines with the full Databricks stack, with a strong focus on software engineering best practices

Preferred Qualifications

• Nice to have: Econometrics/operations research background or relevant experience in trading/optimisation algorithms implementation
• Having worked in the energy sector
• Showing interest for the domain/context you apply ML to
• Experience with MLOps

Benefits

• 30 Days Paid Holiday Leave
• 1 Day Paid Wellness Leave
• 1 Day Paid Birthday Leave
• Paid Maternity and Partner Leave
• Pawternity Leave
• Mental Health and Wellbeing Support
• Remote Office Budget
• Internet Allowance
• Development Plan & Budget
• Stock Appreciation Rights
• 2 Days Paid Volunteer Leave