Senior Staff Machine Learning Engineer – ML Platform

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Develop systems to deploy, iterate, and scale machine learning and optimization models.

• Enhance the infrastructure, tools, and standards of the ML platform.

• Provide operational insights into model performance.

• Create evaluation and backtesting tools for machine learning models, pricing, and trading strategies.

• Take ownership of model inference and training in a production environment.

• Participate in on-call responsibilities during work hours, with the possibility of out-of-hours on-call duties in the future.

• Shape the infrastructure for ML deployment related to pricing, forecasting, prediction, and optimization.

• Design repeatable processes to transition models from experimentation to production.

• Scale models and pipelines in response to growing volume, market dynamics, and complexity.

• Establish reliability, operational monitoring, and analytical oversight for models.

• Identify failures, drift, and degradation at an early stage.

• Validate input data and develop clear data contracts.

• Enhance databases, pipelines, validations, and ingestion processes to ensure safe model rollouts.

• Directly contribute to model enhancements where machine learning expertise can make a significant difference.

⛳️ Requirements

• Solid foundations in ML engineering: experience in developing, deploying, and refining ML models in production.

• Experience in contributing to or constructing an MLOps stack, ensuring reliability and observability.

• Familiarity with the scaling challenges and complexities associated with large-data ML workloads.

• Proficient in designing data systems, including pipelines, databases, and query methodologies.

• Experience with time-series forecasting.

• Understanding of the characteristics of a high-quality ML platform.

• Knowledge in probabilistic modeling and quantifying uncertainty, such as probabilistic forecasts, calibration, or Bayesian methods (bonus).

• Experience in quantitative tools, such as creating backtesting frameworks or evaluation tools for trading or optimization strategies (bonus).

• Background in finance or energy, including automated trading systems (bonus).

• Proficient in English, with strong speaking, reading, and writing skills required.

• Must have the ability to work from the designated country of residence with the appropriate work authorization or sponsorship.

🏝️ Benefits

• Stock options to ensure everyone has a stake in our mission.

• 25 days of vacation plus public holidays.

• Option to exchange public holidays for preferred alternatives.

• Day off for your birthday.

• Remote-first and flexible working environment.

• Clearly defined core working hours.

• No internal meetings scheduled on Friday afternoons.

• Up to GBP1,200 or EUR1,200 annually for remote workspace setup.

• Up to GBP150 or EUR150 monthly for wellness expenses.