{"id":2176037,"url":"https://alion.io/job/tomtom-machine-learning-applied-scientist-adas-online","title":"Machine Learning Applied Scientist - ADAS Online","company":{"id":54490,"name":"TomTom","domain":"tomtom.com","url":"https://alion.io/company/tomtom","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-12T06:55:09Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Amsterdam, Netherlands"],"countries":["NL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Physical AI","optional":false},{"name":"PyTorch","optional":false},{"name":"Transformers","optional":false},{"name":"Vision Transformer","optional":false},{"name":"Perception","optional":true}],"status":"live","first_seen_at":"2026-09-30T10:28:18Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-13T01:49:57Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"We are building a high-performance ADAS Online team focused on advancing state-of-the-art machine learning and AI algorithms for scene understanding and environmental awareness.\nAs a machine learning applied scientist, you will contribute to the development and improvement of models within the in-vehicle spatial awareness stack. Work hands-on across data, experimentation, and evaluation pipelines, and grow your ability to tackle increasingly complex engineering challenges in a fast-moving team.\nThis spatial awareness stack will leverage modern transformer and end-to-end architectures to transform vehicle sensor data along with real-time 3D map data from the cloud into a 3D, semantically defined environment identifying all static and dynamic objects.\nWhat You’ll Do\nDevelop a solid understanding of the team's physical AI roadmap and contribute ideas that improve algorithms within your area of ownership;\nImplement and improve ML / vision transformer models for 3D awareness;\nProduce instance detections and segmentation masks, instance tracking, and occupancy modelling;\nContribute to multi-modal fusion pipelines (camera, LiDAR, RADAR), building and validating components against defined requirements;\nApply Transformer-based and representation learning techniques within established frameworks, building confidence in large-scale model development;\nRun experiments and benchmarks with guidance, producing clear results and contributing to the team's evaluation practices;\nParticipate in translating research into production, learning what makes ML solutions reliable and scalable;\nActively seek feedback from senior engineers and apply it to continuously improve the quality of your work.\nWhat You'll Need\n3+ years of experience in machine learning, vision transformers, diffusion, or computer vision;\nExpertise in modern deep learning architectures;\nHands-on experience with PyTorch (or equivalent frameworks);\nUnderstanding of what is needed to build and deploy large-scale ML models;\nStrong ownership and bias toward execution;\nData-driven mindset with rigorous evaluation practices;\nAbility to operate effectively in fast-paced environments;\nClear communication of technical trade-offs;\nHigh standards for code quality and reproducibility;\nComfortable navigating ambiguity in complex technical domains.\nNice to Have\nExperience in autonomous systems or robotics perception;\nPublications or patents in machine learning or perception;\nExperience with 3D data representations (meshes, point clouds, BEV, voxel grids).","description_format":"text","description_chars":2530,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Netherlands","iso":"NL","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Navigation & Mapping"],"lifecycle":[{"event":"open","at":"2026-10-09T14:11:14Z"}],"visa":[],"liveness":{"score":73,"band":"hot","label":"Hiring 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