Engineering Manager, Active Sensors – LiDAR

Job not on LinkedIn

🔥 4 minutes ago

🚗 Michigan, Texas, +1 more states – Remote

🚗 Michigan – Remote 🤠 Texas – Remote ⚔️ Virginia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Torc Robotics

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2007

🚘 Automotive

📦 Logistics

🚗 Transport

Automotive • Logistics • Transport

Torc Robotics is an innovative company focused on commercializing self-driving trucks for long-haul freight transportation. As an independent subsidiary of Daimler Truck, the company is developing autonomous technology, primarily focusing on the Freightliner Cascadia. Torc is committed to safe transportation, continuously improving its solutions through rigorous testing and integration of industry-leading sensors. It collaborates with fleet management companies to deploy real-world autonomous solutions, aiming to lead the industry in autonomous trucking.

📋 Description

• Lead, coach, and develop a team of machine learning and software engineers, including hiring, performance management, career development, and continuous feedback • Set technical direction, roadmap, and priorities for active-sensor perception • Own development and delivery of multitask models for object detection, road and lane detection, and free-space estimation using lidar and radar data • Guide architecture and design decisions involving shared backbones, task-specific representations, sensor fusion, temporal modeling, uncertainty estimation, and perception-task interactions • Ensure improvements do not introduce unacceptable regressions in other tasks or downstream system behavior • Define strategies for consistent perception performance across adverse weather, changing conditions, sensor degradation, and sensor failures • Drive designs supporting graceful degradation when sensor inputs are missing, degraded, delayed, or unreliable • Own delivery across the machine learning lifecycle, from data requirements and model development through experimentation, evaluation, integration, release, and monitoring • Ensure training and evaluation datasets provide sufficient quality and coverage across operating conditions, geographic features, rare events, adverse weather, and sensor-failure modes • Establish task-level and system-level metrics, benchmarks, and failure-analysis practices • Review technical designs, model architectures, experimental results, training artifacts, and verification evidence • Collaborate with multimodal perception, prediction and planning, data, infrastructure, simulation, sensor hardware, embedded platforms, systems engineering, and safety teams • Track execution and communicate progress, risks, dependencies, and staffing needs to senior leadership • Maintain engineering standards through design reviews, code and model reviews, reproducible experimentation, and release-readiness criteria

🎯 Requirements

• Bachelor's degree in Computer Science, Robotics, Electrical Engineering, or related field with 6+ years of professional experience, or a master's degree with 4+ years of experience • 2+ years of experience leading and managing engineers, including coaching, performance management, and career development • Strong technical foundation in machine learning and computer vision, including 3D geometry, model evaluation, uncertainty, and perception failure modes • Experience developing and deploying production machine learning systems for autonomous driving, robotics, or another real-world application • Experience with multitask learning, object detection, road and lane detection, or 3D occupancy estimation • Strong understanding of lidar sensing, including scan patterns, reflectance, FMCW lidar, and sensor time synchronization • Experience across the machine learning lifecycle, including data curation, model training, controlled experimentation, offline evaluation, system integration, and production validation • Experience analyzing data distributions, dataset coverage, long-tail scenarios, and the relationship between training data and model performance • Strong proficiency in Python and PyTorch, with practical experience using C++ in production perception or machine learning systems • Experience deploying and optimizing deep learning models using TensorRT • Strong understanding of embedded computing platforms and real-time perception system constraints • Experience defining technical roadmaps, planning complex machine learning projects, managing cross-functional dependencies, and delivering against program milestones • Strong written and verbal communication skills, with the ability to explain technical decisions, results, tradeoffs, and risks to technical teams and senior leadership • Bonus: PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or related field • Bonus: Experience with NVIDIA libraries and frameworks such as CUDA, CuDNN, CuBLAS, NPP, and custom TensorRT operations • Bonus: Publications, patents, or open-source contributions in machine learning, computer vision, robotics, or autonomous driving

🏖️ Benefits

• 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 match • Flexibility in schedule • Generous paid vacation available immediately after start date • Company-wide holiday office closures • AD+D and Life Insurance • Potential sign-on payments, relocation, and other forms of compensation may be provided as part of the total compensation package