Applied Scientist / Machine Learning Engineer

📋 Description

• Build scalable methods to discover rare, high-value, and safety-critical scenarios in fleet data
• Use embeddings, active learning, similarity search, model-assisted mining, and smart sampling to
• Design pipelines for automated enrichment, labelling, deduplication, and data-quality monitoring
• Run experiments to understand which data mixtures and curation strategies improve model performance
• Collaborate with foundation-model, evaluation, simulation, and infrastructure teams to move ideas
• Build benchmarks and slice analyses that expose model blind spots and guide the next data and

🎯 Requirements

• Strong machine-learning and software-engineering fundamentals with ability to take applied research
• Proficiency in Python and a modern deep-learning framework
• Comfortable with SQL or large-scale data tools
• Experience with data curation, foundation models, large-scale data wrangling, computer vision, or
• Ability to reason about sampling, class imbalance, label quality, dataset coverage, and
• Comfortable with ambiguous, cross-functional problems and clear communication of technical

🎁 Benefits

• Salaries benchmarked against the market annually
• Meaningful equity
• Relocation support and visa sponsorship where applicable
• Hybrid working and access to vehicle workshops and labs
• Learning and development support
• Comprehensive location-dependent health, family, retirement, and wellbeing benefits