Overview
Join the ALF team to develop high-quality ML software and algorithms powering TomTom’s HD maps for ADAS. You will design, implement, and productionize ML pipelines and components, owning delivery from problem framing to validated outputs. You’ll tackle scale challenges in geospatial data and sensor signals while collaborating with engineers and scientists to meet ambitious product targets. This role offers hands-on impact on real-time location intelligence used by major automotive and tech customers.
Arbeidsvoorwaarden / Benefits
- Competitive compensation
- Personal development budget
- Paid learning days and access to learning platforms
- Enhanced parental leave and compassionate leave
- Flexible work arrangement (office + home)
- Home setup budget
Verantwoordelijkheden
- Design, implement, and integrate ML algorithms and data pipelines within your focus area
- Lead projects and own components from upstream data to downstream outputs
- Drive improvements in recall, precision, latency, and cost against customer-facing targets
- Mentor junior engineers, review code, and contribute to hiring as an interviewer
- Tackle large-scale geospatial and sensor data challenges and build robust evaluation pipelines
- Document outcomes and enable repeatable success for the team
- Work in an agile environment with iterative experimentation and production rollout
Belangrijkste vereisten
- 4+ years in Applied Science, ML, algorithm development, or related
- Bachelor’s degree in a quantitative field (minimum); Master/PhD a plus
- Strong algorithm design fundamentals and geospatial/signal-processing knowledge
- Solid ML fundamentals: training, evaluation, statistics, experimental design
- Proficiency in Python and ML frameworks (PyTorch, TensorFlow)
- Experience taking models/pipelines to production and leading delivery
- Mentoring experience and ability to perform insightful code reviews
- Breadth across applied science with depth in some areas; ability to learn new sub-domains quickly
- English communication skills
- Curiosity and ability to learn across the ML stack
- Problem-solving autonomy and capability to bring new perspectives
- Mentoring and coaching
- Strong communication
- Curiosity and willingness to expand skill set
- Python
- PyTorch
- TensorFlow
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