Torc Robotics

Data Engineer

• Own the design and organization of the program’s data lake, including schema definitions, partitioning strategy and metadata indexing.
• Design and maintain end-to-end pipelines that ingest high-bandwidth sensor logs from vehicles into cloud storage with high reliability and tolerant of ad-hoc and intermittent connectivity mechanisms.
• Develop data validation and integrity checks that can detect corrupted information, missing sensors, and inconsistent calibration prior to the data being processed by downstream systems.
• Implement retention, tiering and lifecycle policies for data to balance storage costs with development value.
• Build tooling to query raw logs to produce curated training and evaluation datasets.
• Build automation to run cost-effective pseudo-labeling workflows at the scale of data ingest.
• Implement data quality and model performance metrics that are used to direct labeling effort toward the highest-value examples.
• Deploy and maintain data visualization tooling to support log review, annotation QA, and autonomy debugging workflows.
• Build integrations between the visualization tooling and the data lake so engineers can navigate from a dataset entry or model failure directly to the origin log data
• Work with autonomy engineers to define and surface custom visualization panels and implement metrics for analyzing unstructured operating environments.
• Build dashboards that provide the autonomy engineers visibility into data coverage by terrain type, operating environment and geographic region.
• Establish and document data contracts between the data services and model training consumers.
• Partner with perception, planning and embedded engineers across the data lifecycle: from shaping the logging schemas and collection triggers to defining the dataset interfaces that supply model training and evaluation.
• Define data engineering standards, best practices, and tooling choices for an innovative and fast-paced team.
• Contribute to the data roadmap and provide input to technical leadership on investment priorities.
• Mentor junior engineers and raise the team’s capabilities in data infrastructure scalability and operational hygiene.

Senior Autonomy Data Engineer

Full-stack Engineer

• Design, develop, and maintain core planning and prediction systems, including trajectory generation, behavior prediction, decision-making, and motion planning algorithms for autonomous trucks.
• Advance and evaluate multiple planning approaches, including optimization-based, learning-based, and hybrid architectures, making data-driven decisions on where each methodology delivers the greatest value.
• Own technical solutions across the full software lifecycle, including architecture design, implementation, testing, simulation validation, vehicle integration, deployment, and long-term maintenance.
• Develop production-quality software using modern C++ within a Linux environment while adhering to quality, safety, testing, and deployment best practices.
• Drive simulation-based validation efforts across Software-in-the-Loop (SiL), Hardware-in-the-Loop (HiL), and Vehicle-in-the-Loop (ViL) environments to ensure robust performance and prevent regressions.
• Partner closely with Safety, Controls, Perception, Validation, and Simulation teams to develop safe and reliable autonomous driving behaviors, including fallback strategies and minimum-risk maneuvers.
• Lead root-cause investigations by reproducing field issues in simulation, debugging vehicle behavior, and translating findings into actionable software improvements.
• Influence technical strategy, roadmap planning, and long-term architectural direction across the Behaviors organization.
• Act as a technical lead on complex, cross-functional initiatives, driving alignment and execution across teams and stakeholders.
• Mentor engineers, raise technical standards, and help develop the next generation of autonomy leaders within the organization.

Staff Software Engineer – Behaviors

Machine Learning Engineer

• Implement the latest research advances in Neural Rendering and generative models
• Translate cutting edge solution in the domain of autonomous driving for high-quality Camera, LiDAR and Radar sensor simulations
• Support implementing a neural rendering framework that allows to scale perception simulation and AV 3.0 training
• Integrate the framework in a cloud environment and automate the pipeline to allow scaling for the target verification and validation of our autonomous trucks
• Own development projects in the team – From research, design, to implementation, testing and deployment
• Design, implement, test and deploy shippable production quality software starting from early prototypes using disciplined software development processes.
• Work in the cloud machine learning ecosystem alongside other machine learning services existing in the company.
• Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation.
• Demonstrate project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution, coaching and mentoring as needed.

Senior ML Engineer – Neural Rendering

Systems Engineer

• Contribute to the development and maintenance of automated test frameworks for component-level validation using HIL systems
• Develop Python-based tooling supporting test automation, validation workflows, and data analysis
• Support execution and monitoring of automated software validation across embedded and autonomy subsystems
• Assist in analyzing test failures, debugging issues, and investigating root causes across hardware and software components
• Collaborate with systems, embedded, and autonomy teams to support validation strategies and improve test coverage
• Help maintain scalable test infrastructure and CI-based validation workflows
• Support integration and verification activities involving sensors, compute platforms, and control systems
• Participate in test planning, automation improvements, and validation activities across the software development lifecycle

Systems Engineer I – Test Automation

• Contribute to the development and maintenance of Python-based services and AWS data pipelines supporting metrics and validation workflows
• Assist in processing and analyzing vehicle telemetry and validation data to generate meaningful safety metrics
• Support implementation of release validation logic tied to automated testing and evaluation pipelines
• Collaborate with systems, validation, and autonomy teams to support implementation of safety and performance metrics
• Investigate pipeline failures, telemetry inconsistencies, and data quality issues using logs and large-scale datasets
• Support workflow orchestration and automation systems used for validation and release readiness
• Participate in code reviews and collaborate with team members to deliver reliable, maintainable software solutions
• Contribute to continuous improvement of engineering practices, tooling, and validation infrastructure

Software Engineer I – Metrics for Release Implementation

Security Engineer

• Define and evaluate the implementation of cybersecurity controls, including but not limited to, embedded operating system, encryption, access controls, network security, and secure coding practices.
• Specific hands-on knowledge with implementation of cybersecurity embedded operating systems, networking, and cryptographic controls.
• Conduct, with a cross-functional team, process activities to define requirements, find design deficiencies, detect implementation defects, verify the product’s cybersecurity posture, and otherwise secure Torc’s products.
• Collaborate with product development teams to embed security into their design and development lifecycle of products and other software development activities.
• Stay abreast of emerging cybersecurity threats and technologies and continuously update our software security approaches, strategies, and solutions accordingly.
• Liaise with external security vendors and partners, managing relationships, and ensuring the effective integration of third-party security solutions.
• Prepare and present evidence in the cybersecurity case to demonstrate readiness to launch new products or release new software versions from a cybersecurity perspective.
• Train internal stakeholders on security practices and act as a resource where expert cybersecurity assistance is needed.

Senior Product Cybersecurity Architect

• Defining and maintaining an account vending machine with appropriate organizational control policies
• Designing and operating shared networks, including Direct Connect, Site-to-Site VPN, and cloud-native network segmentation
• Owning cloud security posture: SIEM integrations, identity and access management, and compliance tooling
• Designing, deploying, and operating shared infrastructure including EKS and ECS clusters, and hosted application platforms
• Maintaining and improving CI/CD infrastructure and shared build tooling used across the engineering organization
• Managing shared package and artifact distribution (JFrog Artifactory, AWS CodeArtifact)
• Driving cloud cost visibility, attribution, and efficiency across the organization
• Collaborating with teams specializing in perception, planning, control, mapping, and vehicle testing to architect solutions that support their development workflows in AWS
• Contributing to technical decisions, design reviews, and the team's documentation and operational standards

Senior Software Engineer – Cloud Automation

Business Intelligence Developer

• Develop and implement novel solutions to monitor and improve business performance and efficiency starting from gathering requirements from stakeholders to partnering with data producing teams and other analysts to build and operationalize functional systems.
• Define, instrument, and maintain new and existing business KPIs from scratch, leveraging SQL queries and Python scripting.
• Build automation to ensure we can understand and act on business performance with accurate, scalable, and low latency solutions that require minimal maintenance.
• Create actionable, user-friendly, and intuitive dashboards using Tableau or other tools - to surface business performance and support scalable data-driven decision making.
• Ensure transparency of data quality by clearly documenting data sources and data validation processes and regularly auditing the results.
• Work with IT staff to design and implement secure and sustainable paths for data access from systems to support timely dashboards.
• Use out-of-the-box thinking to develop and implement solutions to unique challenges.
• Create documentation and provide training to inform stakeholders and cultivate data literacy within the organization.
• Answer complex business questions via ad-hoc SQL queries or Python notebooks to enable business owners to make critical decisions.

Senior BI Analyst

Program Manager

• Lead cross-functional teams to scope complex Integration initiatives, across Engineering, Software, Safety, Test, Product, Operations, and Commercial teams
• Define goals and objectives that drive cross-functional teams to deliver on complex, highly coupled initiatives.
• Engage all appropriate stakeholders to ensure all departments are focused on the highest priority integration needs.
• Clearly articulate status of program initiatives through frequent updates, dashboards, and metrics.
• Identify, map, track, and drive dependencies and risks to resolution.
• Analyze product milestones and ensure cross-functional work is planned and if approved, executed in-order-to meet objectives.
• Identify and mitigate risks, issues, and opportunities toward initiative success.
• Monitor progress of initiative assignments against program objectives, communicating issues, risks, and mitigation plans with key stakeholders.
• Works collaboratively across program management, technical program management, and product management teams to ensure a strong partnership.
• Independent preparation and post-processing of meetings and workshops including organization, moderation, decision tracking, documentation of outcomes, as well as follow-up on actions.

Product Manager

• Drive the product vision internally by developing high-quality product definition, scoping, and prioritization.
• Drive the development of product features and functionality by liaising between the engineering team and relevant stakeholders. Gather user requirements, build product requirements, and communicate with engineering and other stakeholders at all levels of planning and execution.
• Define clear, testable, and concise high-quality product requirements, success metrics and prioritization based on customer feedback, market research, and business priorities, and effectively communicate them to the relevant TPM and engineering teams.
• Develop and propose process improvement initiatives to ensure cross-functional alignment between teams and projects. Support the process rollout and iterative cycle for continuous improvement.
• Actively participate in regular planning exercises to support product prioritization across the company.
• Analyze and understand customer, commercial, and technical constraints and tradeoffs by collaborating with engineering, commercial, legal, safety and regulatory to inform product roadmaps and backlogs. Recommend path forward with agreement from senior managers.
• Define, analyze, communicate, and continuously update key product plans and metrics to ensure priorities remain up to date.
• Develop and execute compelling customer demos and customer meeting outcomes.
• Collaborate, research, review competitor communications, and analyze and compare competing products to ensure Torc maintains the best products available.
• Help set, track, and achieve goals aligned with company-wide vision, goals, and initiatives.
• Champion customer-focused development across Torc and support the business to embrace customer-centric work culture.
• Act as a role model for Torc’s Values.

Senior Product Manager – TorcDrive

• Lead ODD characterization efforts by analyzing large-scale datasets across real-world, simulated, and mapped environments
• Define system-level strategies for leveraging map data (HD/SD), telemetry, and autonomy logs to assess operating conditions
• Design and implement Python-based workflows to extract, transform, and analyze data from cloud-based systems
• Work across internal and supplier-provided datasets (mapping, perception, vehicle data) to derive actionable insights
• Define KPIs and metrics that evaluate safety, performance, and release readiness of autonomy systems
• Translate data insights into system-level requirements, design decisions, and validation strategies
• Collaborate with mapping, perception, AI/ML, and validation teams to align on data usage and system behavior
• Drive technical direction across teams by connecting data, system architecture, and real-world performance
• Identify gaps in data, tooling, and system design and propose scalable solutions

Senior Autonomy Systems Engineer – Data, Cloud, Mapping

• Build and maintain Python-based data pipelines to ingest, process, and analyze large-scale autonomy datasets
• Develop tools to extract and manipulate data from cloud-based storage systems (AWS, GCP, etc.)
• Work with HD/SD map data, vehicle telemetry, and simulation outputs to support autonomy workflows
• Write performant and scalable code for data processing, transformation, and analysis
• Collaborate with systems, mapping, and AI/ML teams to support data-driven decision making
• Develop scripts and tools to support scenario generation, ODD analysis, and validation workflows
• Optimize data workflows for performance, scalability, and reliability
• Contribute to system-level debugging by analyzing data and identifying root causes of issues
• Support integration of data pipelines into broader autonomy and validation systems

Senior Autonomy Software Systems Engineer, Python, C++

Software Engineer

• Own the technical vision and roadmap for Learned Vehicle Intent (LVI), aligning model development with product and safety goals
• Lead and scale 2–3 teams of ML engineers, driving execution across model development, training, and deployment
• Set and uphold a high bar for technical excellence in reinforcement learning, imitation learning, and behavior modeling
• Guide architecture decisions for policy learning systems, including behavior cloning, RL, and multi-agent interaction models
• Drive development of scalable training pipelines, data infrastructure, and experimentation frameworks
• Partner cross-functionally with perception, prediction, analytical planning, simulation, and safety teams to integrate learned behaviors into the autonomy stack
• Ensure robust validation and evaluation of behavior models, including failure analysis and performance tracking across simulation and real-world environments
• Establish best practices for data strategy, model iteration, and system-level integration
• Mentor senior and staff engineers, fostering growth, ownership, and technical leadership within the team
• Lead team planning, execution, and delivery, ensuring alignment with broader organizational priorities

Senior Manager, Engineering – Learned Vehicle Intent

• Own the design and architecture for a scalable sensor calibration pipeline in C++, leveraging available libraries (OpenCV, linear algebra libraries) for real-time and offline calibration.
• Deep expertise in linear algebra to lead the design and implementation of spatial computational systems for multi-modals sensor platforms. Apply advanced mathematical rigor using Lie groups, quaternions, and 3D transformations to ensure accurate spatial calibration.
• Lead the development of specialized dedicated libraries allowing sensor-to-sensor extrinsic calibration (lidar-camera, imu-lidar, etc.) using multi-sensor targetless detections during robotics missions.
• Experience with camera intrinsic and extrinsic calibration.
• Drive the design and maintenance of simulation tools and data pipelines for sensor modeling, calibration validation, and large-scale regression testing.
• Collaborate cross-functionally with perception, simulation, and platform teams to define calibration requirements, set best practices, and ensure robustness across hardware configurations and software releases.
• Establish and maintain CI/CD-integrated calibration workflows using Docker, Bazel, and Git to enable reproducible, automated testing and deployment.
• Lead deep-dive debugging and root-cause analysis of complex sensor alignment issues in vehicle logs and simulation using ROS tools, rviz, and custom visualization utilities.
• Mentor junior engineers and contribute to technical reviews, fostering a culture of high-quality software design and code excellence.

Senior Software Engineer, Calibration

• Own the design and architecture for a scalable sensor calibration pipeline in C++, leveraging available libraries (OpenCV, linear algebra libraries) for real-time and offline calibration
• Deep expertise in linear algebra to lead the design and implementation of spatial computational system for multi-modals sensor platforms
• Lead the development of specialized dedicated libraries allowing sensor-to-sensor extrinsic calibration (lidar-camera, imu-lidar, etc.) using multi-sensor targetless detections during robotics missions
• Experience with camera intrinsic and extrinsic calibration
• Drive the design and maintenance of simulation tools and data pipelines for sensor modeling, calibration validation, and large-scale regression testing
• Collaborate cross-functionally with perception, simulation, and platform teams to define calibration requirements, set best practices, and ensure robustness across hardware configurations and software releases
• Establish and maintain CI/CD-integrated calibration workflows using Docker, Bazel, and Git to enable reproducible, automated testing and deployment
• Lead deep-dive debugging and root-cause analysis of complex sensor alignment issues in vehicle logs and simulation using ROS tools, rviz, and custom visualization utilities
• Mentor junior engineers and contribute to technical reviews, fostering a culture of high-quality software design and code excellence