Senior Research Engineer - Perception & Foundation Models jobs in United States
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Zendar · 2 days ago

Senior Research Engineer - Perception & Foundation Models

Zendar is a company focused on developing advanced radar-based vehicular perception systems for the automotive industry. They are seeking a Senior Machine Learning Research Engineer to design and implement multi-sensor perception models that fuse camera and radar data, enabling robust real-world autonomy.

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H1B Sponsor Likelynote

Responsibilities

Own architecture and technical strategy for multi-sensor perception models, including explicit tradeoffs (why approach A vs B), risks, validation plans, and timelines
Build foundation-scale / transformer-based perception models trained from scratch on large-scale multi-modal driving datasets (not limited to fine-tuning)
Develop fusion architectures for streaming multi-sensor inputs (camera/radar/lidar), with early fusion and temporal fusion; align training objectives to real-world reliability targets
Deliver production-ready models for:
Occupancy / free-space / dynamic occupancy (full-scene understanding)
3D Object detection and tracking
Lane line / road structure estimation
Drive long-tail reliability (e.g., toward “four nines” behavior in defined conditions)
Partner with platform/embedded teams to ensure models meet real-time constraints (latency, memory, throughput) and integrate cleanly via stable interfaces for downstream consumers

Qualification

Deep learningTransformer-based architecturesMulti-sensor fusionLarge models trainingPythonPyTorchTensorFlowArchitectural discussionsReal-time constraintsEnd-to-end perception stack

Required

Deep expertise in deep learning for perception, especially transformer-based architectures, temporal modeling, and multi-modal learning
Proficiency with Python and a major deep learning framework (e.g., PyTorch, TensorFlow)
5+ years (or having a PhD) experience designing and implementing ML systems, with demonstrated ownership of research/production outcomes
Demonstrated experience training large models from scratch (not only fine-tuning)
Strong experience with multi-sensor fusion (camera/radar/lidar) and real-world sensor
Strong understanding of the end-to-end perception stack and downstream needs (interfaces, uncertainty, temporal stability, failure modes)
Ability to lead architectural discussions: articulate tradeoffs, quantify risks/benefits, and set realistic milestones and timelines

Preferred

PhD in a relevant field (Machine Learning, Computer Vision, Robotics) preferred
Experience with foundation models for autonomy and robotics, including multi-modal pretraining, self-supervised learning, and scaling laws / model scaling strategies
Experience with transfusion-style or related fusion paradigms (transformer-based fusion across modalities and time), including building from first principles
Experience with BEV-centric perception, 3D detection, occupancy networks, tracking, and streaming inference

Benefits

Performance based Bonus
Benefits including medical, dental, and vision insurance, flexible PTO, and equity
Hybrid work model: in office 3 days per week from Tuesday to Thursday, the rest… work from wherever!
Daily catered lunch and a stocked fridge (when working out of the Berkeley, CA office)

Company

Zendar

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Zendar develops high-definition radar for autonomous vehicles.

H1B Sponsorship

Zendar has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
2024 (2)
2023 (1)
2022 (6)
2021 (1)

Funding

Current Stage
Growth Stage
Total Funding
$22.55M
Key Investors
NXP SemiconductorsHyundai MobisKhosla Ventures
2023-11-02Series Unknown
2022-01-27Series B· $4M
2021-06-18Series Unknown· $8M

Leadership Team

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Jimmy Wang
Chief Product Officer and Co-Founder
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Company data provided by crunchbase