[Hiring] Engineering Manager, Active Sensors @Torc Robotics

Role Description

The Perception department is seeking an experienced and technically strong Engineering Manager to lead a machine learning team developing active sensor-based perception capabilities for our autonomous trucks.

• Lead, coach and develop a team of machine learning and software engineers, including hiring, performance management, career development, and continuous feedback.
• Set the technical direction, roadmap, and priorities for active-sensor perception in alignment with perception and vehicle-level milestones.
• Own the 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 interactions among perception tasks.
• Ensure that improvements to one task do not introduce unacceptable regressions in other tasks or in downstream system behavior.
• Define the team’s strategy for maintaining consistent perception performance across adverse weather, changing environmental conditions, sensor degradation, and sensor failures.
• Drive model and system designs that support graceful degradation when sensor inputs are missing, degraded, delayed, or unreliable.
• Own delivery across the machine learning lifecycle, including data requirements, model development, experimentation, evaluation, integration, release, and monitoring.
• Ensure that training and evaluation datasets provide sufficient quality and coverage across operating conditions, geographic features, rare events, adverse weather, and sensor-failure modes.
• Establish rigorous task-level and system-level metrics, benchmarks, and failure-analysis practices covering precision, recall, range, latency, robustness, cross-task performance, and downstream impact.
• Review technical designs, model architectures, experimental results, training artifacts, and verification evidence to ensure that decisions are supported by data.
• Collaborate with teams across multimodal perception, prediction and planning, data, infrastructure, simulation, sensor hardware, embedded platforms, systems engineering, and safety.
• Track execution against commitments and communicate progress, risks, dependencies, and staffing needs to senior leadership.
• Maintain high engineering standards through design reviews, code and model reviews, reproducible experimentation, and clear release-readiness criteria.

Qualifications

• 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 one or more relevant areas, such as multitask learning, object detection, road and lane detection, or 3D occupancy estimation.
• Strong understanding of lidar sensing and its impact on perception, 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, along with practical experience using C++ in production perception or machine learning systems.
• Experience deploying and optimizing deep learning models using TensorRT, including evaluating tradeoffs among model performance, robustness, latency, memory, power, and hardware utilization.
• Strong understanding of embedded computing platforms and the constraints associated with deploying real-time perception systems.
• 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 both technical teams and senior leadership.

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 and generous paid vacation (available immediately after start date).
• Company-wide holiday office closures.
• AD+D and Life Insurance.

Company Description

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.