Logo HERE Global B.V.

Sr./Principal Engineer- Autonomous Vehicle Simulation Domain Expert

HERE Global B.V.

Job

  • Level
    Senior
  • Job Field
    Software, Data
  • Employment Type
    Full Time
  • Contract Type
    Permanent employment
  • Location
    Berlin, Schwalbach
  • Working Model
    Hybrid, Onsite

    • Job Summary

    In this role, you will develop generative models for autonomous vehicle simulations, integrating ML techniques with map and scenario data, and oversee the entire training process from data preparation to evaluation.

    Job Technologies

    Your role in the team

    • HERE Technologies sits at a unique intersection: we own some of the world's most detailed map and drive data, and we are building generative AI capabilities to turn that spatial intelligence into controllable, high-quality synthetic driving worlds.
    • We are looking for a hybrid profile - someone who combines deep learning expertise in world foundation models, generative video, and transformers with hands-on AV (Autonomous Vehicle) simulation experience.
    • This is not a pure simulation role, nor a pure ML research role.
    • It is the bridge between the two - and that bridge is where HERE's differentiation lives.
    • You understand both how to train and adapt large generative models (think Cosmos, Cosmos-Transfer, diffusion-based video models, latent world models) and how to ground them in map data and scenario semantics so the output is actually useful for training and validating perception and planning stacks.
    • Drive technical direction for map-grounded world foundation models, conditioning generative video/world models on map data, drive data, scenario semantics, trajectories, agent behaviours, weather, and lighting.
    • Train, fine-tune, and adapt generative models (diffusion, latent video, transformer-based) for driving scenario generation with full ownership of the ML lifecycle: data curation, training, evaluation, and production pipelines.
    • Evaluate and extend state-of-the-art models such as NVIDIA Cosmos / Cosmos-Transfer and comparable open-source alternatives for AV training data generation.
    • Lead POC initiatives for map-grounded synthetic scenario generation with key technology partners; define measurable success criteria beyond visual realism - focusing on ML training utility, controllability, and sim-to-real transfer.
    • Deliver GO / PIVOT / NO-GO recommendations backed by quantitative evidence.
    • Bridge generative world models with classical simulation stacks (CARLA, NVIDIA Drive Sim, AlpaSim) for physics-grounded scenarios.
    • Author and programmatically generate OpenSCENARIO / OpenDRIVE definitions for both classical and generative pipelines.
    • Drive sim-to-real strategy: measure domain gap, identify failure modes, and define acceptable thresholds for downstream model training.
    • Define "good enough" synthetic data for AV perception and planning: when photorealism is required, when label consistency suffices, and when controllability matters most.
    • Establish validation frameworks combining objective metrics (distribution coverage, label accuracy, FID-style measures, downstream task performance) with expert evaluation protocols.
    • Specify sensor fidelity requirements: noise models, lens distortion, and lidar return characteristics.
    • Interface with ML research, perception, and planning teams to ensure synthetic data measurably improves real-world model performance.
    • Translate business requirements into technical feasibility assessments for product and executive stakeholders.

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    Our expectations of you

    Qualifications

    • This role sits at the intersection of deep learning and AV simulation - and we need someone equally grounded in both.
    • You have taken ML models from research into production, navigating real-world constraints, quality thresholds, and safety requirements along the way.
    • Expertise in generative video, world models, or related generative AI - specifically diffusion models, latent video models, and/or transformer-based world models.
    • Strong Python and PyTorch fundamentals; track record of taking ML models from research to production under real-world constraints.
    • Fluency in OpenDRIVE and OpenSCENARIO: able to author and generate scenario definitions programmatically.
    • Understanding of AV testing workflows, ASAM OpenX standards, ISO 34502, and what scenarios stress-test perception and planning systems.
    • Ability to evaluate synthetic data for distribution diversity, label consistency, edge-case coverage, and downstream task performance.
    • Klare Sichtweise auf die Abwägungen zwischen Photorealismus, Label-Genauigkeit, Kontrollierbarkeit und Rechenleistung.

    Experience

    • Proven end-to-end model training experience with clear ownership across data, training, evaluation, and iteration.
    • Experience with high-dimensional spatio-temporal data (video, multi-sensor fusion, driving data).
    • 5+ years spanning AV simulation, AV perception/ML, or robotics simulation - with meaningful exposure to both simulation platforms and ML model development.
    • Hands-on experience with at least one major simulation platform: CARLA, NVIDIA Drive Sim, or equivalent.
    • Experience with sim-to-real transfer, domain adaptation, or closing the domain gap measurably.

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    What we offer

    • This role can be based in Berlin/Frankfurt/Munich/Amsterdam.
    • As part of HERE Technologies' employment process, candidates will be required to successfully complete a pre-employment screening process.
    • This offer and any related claims are subject to the successful completion of a pre-employment screening.
    • This will involve employment, education, and criminal verification if applicable.

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    Benefits

    Work-Life-Integration

    Health, Fitness & Fun

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    Topics that you deal with on the job

    Job Locations

    • Location Schwalbach

      66773 Saarland

      Germany

    • Location Berlin

      Germany

    This is your employer

    HERE Global B.V.

    HERE Global B.V.

    Here Technologies, which goes by the name Here, is a company that provides mapping and location data.

    Description

  • Language
    English
  • Company Type
    Established Company
  • Working Model
    Hybrid, Onsite
  • Industry
    Internet, IT, Telecommunication
    • Logo HERE Global B.V.

    Sr./Principal Engineer- Autonomous Vehicle Simulation Domain Expert

    HERE Global B.V.
    Location
    Berlin, Schwalbach
    Working Model
    Hybrid, Onsite
    Diversity
    Open for all genders
    English Only
    English only required

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