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Staff, Machine Learning Engineer - BEV/Multi-Modal Perception

Remote, U.S, Ann Arbor, MI

Live, first seen by us 59 days ago
Pay
USD 215,500–258,600/yearAnnual period assumed — pay source
US Pay Range $215,500—$258,600 USD
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Work setting
Working pattern needs review — work setting source
Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy). Work Location: For this position, we are open to hiring in Ann Arbor, MI in a hybrid capacity. We are also open to hiring Remote in the United States. Perks of Being a Full-time Torc’r
Listed location: Remote, U.S, Ann Arbor, MI
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Employment
Not stated

What you’ll work on

Full posting
  • Define and execute the technical roadmap for BEV-based perception models

  • Design multi-modal architectures that fuse camera, LiDAR, radar and HD map data

  • Own large-scale model training, from data sampling to distributed training

  • Improve robustness on long-tail conditions like low visibility and occlusions

  • Mentor ML engineers on experimentation, code quality and model validation

From the employer’s posting
define and execute the technical roadmap for BEV-based perception models
Design advanced multi-modal architectures that fuse heterogeneous sensor data (camera, LiDAR, radar, HD maps) into unified spatial 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.
Mentor and guide ML engineers, cultivating best practices in experimentation, code quality, and model validation.
Education & alternatives
- 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems. - M.S. or Ph.D. 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.

About Torc Robotics

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.

In the employer’s words · Read in context

Apply at Torc Robotics

Posting record

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Status in our records
Live
First seen by us
Sep 5, 202659 days ago
Recorded sightings
38
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$216K–$259K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 59

Similar jobs usually come down between day 6 and day 69.

From 4,301 similar postings that came down. Coming down is not always a hire.

Torc Robotics is hiring

15 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • ML Engineer hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

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  • Python
  • PyTorch
  • TensorFlow
Where the posting names them
- 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.

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

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About the Company 

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.

A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. 

Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. 

Meet the Team
As a Staff Machine Learning Engineer specializing in BEV (Bird's-Eye View) and Multi-Modal Perception, you will lead the development of next-generation models that unify information across cameras, LiDAR and radar to deliver a rich spatial understanding of the driving environment. You will drive architectural innovation, large-scale model training, and data-driven improvements that directly advance the perception capabilities at the heart of Torc's autonomous driving stack. This is a technical leadership role focused on model innovation and maturity, not downstream feature integration.

What You'll Do

  • 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 (camera, LiDAR, radar, HD maps) 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.

What You'll Need to Succeed

  • 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems.
  • M.S. or Ph.D. 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.

Bonus Points

  • Experience with autonomous driving or robotics perception in production environments.
  • Experience with MLOps and infrastructure tools (Ray).
  • Hands-on expertise in BEV-based ML architectures, LiDAR-vision fusion, or spatial-temporal modeling.
  • Familiarity with 3D labeling, calibration, and sensor simulation pipelines.
  • Track record of publications or open-source contributions in top-tier venues (CVPR, ICCV, NeurIPS, ICRA, CoRL).
  • Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy).

Work Location: For this position, we are open to hiring in Ann Arbor, MI in a hybrid capacity. We are also open to hiring Remote in the United States.

Perks of Being a Full-time Torc’r 

Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:   

  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees   
  • 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
  • AD+D and Life Insurance  

At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. 

Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. 

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. 

Job ID: 102945

Hiring Range for Job Opening 
US Pay Range
$215,500—$258,600 USD
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Pay
US Pay Range $215,500—$258,600 USD
Location & working pattern

Remote, U.S, Ann Arbor, MI

- Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy). Work Location: For this position, we are open to hiring in Ann Arbor, MI in a hybrid capacity. We are also open to hiring Remote in the United States. Perks of Being a Full-time Torc’r
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