Staff ML Engineer: 3D Perception & Multi-Modal Fusion

Openkrill; United States; Hybrid; USD 216,000 - 259,000; Full time

Benefits offered by this job

Stock options

Full medical coverage

401K match

Paid vacation

Job summary

Torc is seeking a Staff Machine Learning Engineer specializing in BEV and multi-modal perception to drive next-generation perception models for autonomous driving. You will lead model development across BEV-based tasks and coordinate cross-functional teams to deliver robust 3D understanding.

You will mentor engineers, advance large-scale training pipelines, explore self-supervised learning, and stay at the forefront of ML research.

Qualifications

• 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems.
• MS or PhD in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience).
• Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
• Strong background in multi-modal sensor fusion, particularly integrating camera and LiDAR data.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with large-scale data pipelines, distributed training, and experiment management systems.
• Demonstrated leadership in driving ML model innovation and mentoring technical teams.

Responsibilities

• Lead BEV model development: define and execute the technical roadmap for BEV-based perception models across multiple tasks (e.g., detection, segmentation, road topology, and scene understanding).
• Design advanced multi-modal architectures that fuse heterogeneous sensor data into unified spatial representations.
• Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations.
• Own large-scale training workflows — from data sampling strategies and augmentation pipelines to distributed training and hyperparameter optimization.
• Advance model robustness and generalization, addressing long-tail conditions such as low visibility, occlusions, and rare scene configurations.
• Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.
• Collaborate cross-functionally with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.
• Mentor and guide ML engineers, cultivating best practices in experimentation, code quality, and model validation.
• Stay at the forefront of ML research, exploring self-supervised learning, large-scale pretraining, or foundation models for 3D perception.

Skills

Deep learning

3D vision

Multi-modal fusion

Leadership

Python

Model training

Education

MS/PhD in CS/EE/Robotics

Tools

PyTorch

TensorFlow

Job description

Torc is seeking a Staff Machine Learning Engineer specializing in BEV and multi-modal perception to drive next-generation perception models for autonomous driving. You will lead model development across BEV-based tasks and coordinate cross-functional teams to deliver robust 3D understanding.

You will mentor engineers, advance large-scale training pipelines, explore self-supervised learning, and stay at the forefront of ML research.