🔔 Senior Machine Learning Engineer

What if your forecasting models didn’t just sit in dashboards — but directly shaped real-world commercial decisions and reduced global waste?

I’m working with an ambitious, product-led climate tech company building intelligent forecasting systems that turn messy, real-world signals into reliable, high-impact decisions. Their platform powers a commercial MVP today — and they’re now scaling both the product and the ML capability behind it.

They’re looking for a Senior Machine Learning Engineer to own forecasting systems end-to-end, shape ML standards, and grow into a technical leadership role as the company scales.

This is a role for someone who enjoys operating across levels: hands-on model builder, ML platform architect, mentor, and strategic technical partner.

What the Senior Machine Learning Engineer will be working on:

• Designing, building, and operating production-grade time-series and causal forecasting models for supply, demand, and pricing.
• Owning the full ML lifecycle — from data ingestion and feature engineering to deployment and monitoring.
• Architecting scalable ML infrastructure (training pipelines, validation, CI/CD, automated retraining, canary releases, A/B testing).
• Implementing model observability: drift detection, bias checks, explainability, alerting, and SLAs.
• Designing cloud-native ML architecture within a modern Azure environment.
• Partnering closely with product, engineering, and customers to translate business goals into measurable ML outcomes.
• Defining analytics and success metrics that clearly demonstrate product and commercial impact.
• Mentoring peers and helping raise the engineering bar across data, modelling, and MLOps.

🧠 What the successful Senior ML Engineer will need:

• 6+ years of experience building and deploying forecasting models into production.
• Strong foundations in software engineering and ML engineering best practices (testing, CI/CD, production services).
• Strong experience with time-series modelling, feature engineering for temporal data, uncertainty estimation, and backtesting.
• Experience building scalable ML/data platforms.
• Hands-on experience with explainability and stakeholder-facing model communication.
• Strong Python skills (R for analysis is a plus).
• Experience across tools such as scikit-learn, Prophet, TensorFlow/Keras, XGBoost, LightGBM, Spark, SQL, Airflow (or similar).
• Cloud experience (Azure environment preferred).
• A startup mindset: pragmatic, ownership-driven, and comfortable in fast-moving environments.

🌟 What’s on offer for the successful Senior Machine Learning Engineer:

• A genuinely high-impact role where your models directly power commercial decisions.
• Significant ownership and scope to grow into broader technical leadership.
• Hybrid working model with flexibility.
• An international team of experienced product and technology leaders.
• The opportunity to contribute to reducing global waste — and help save the planet one ton at a time.

This is more than a forecasting role — it’s an opportunity to build production ML systems that matter, influence technical direction, and create measurable climate impact.

📩 Interested? Send your CV to the email below and I’ll be happy to share more details.