Lead Machine Learning Engineer

What You'll do

• Lead the design and delivery of end-to-end ML systems powering recommendations, ranking, and personalization, driving measurable improvements in user outcomes

• Architect and optimise ML pipelines, integrating data processing, model training, evaluation, and deployment into scalable systems (e.g. Spark, Airflow) 

• Build and deploy advanced models using modern frameworks (e.g. PyTorch), ensuring robustness in high-scale production environments 

• Develop and apply LLM-based capabilities, including prompt design and fine-tuning approaches for production use cases 

• Drive experimentation strategy, including A/B testing and offline evaluation, to continuously improve performance and inform product decisions

• Partner cross-functionally with Product, Engineering, and Data teams, collaborating with purpose to translate business challenges into ML solutions

• Mentor and support other engineers, fostering a culture of Curiosity, ownership, and continuous improvement

About You

• Typically requires 7–10 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.

• Strong expertise in machine learning, with a track record of delivering end-to-end systems in production

• Proficiency in Python and ML frameworks (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking, or NLP

• Experience designing and scaling ML pipelines and data systems (e.g. Spark, Airflow, or similar technologies)

• Hands-on experience with LLMs, including prompting, evaluation, and production integration 

• Demonstrated ability to take ownership of ambiguous problems and deliver impactful outcomes

• Strong collaboration skills, working cross-functionally and taking ownership of shared goals

• Solid AI fluency, with the ability to guide best practices in model development and responsible AI usage within a team