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Agility Robotics

Hybrid

<div class="content-intro">Agility’s commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.</div>About The Role
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Join the Autonomy team as a Senior Software Engineer focused on Navigation. You will be a core contributor, driving the design and deployment of real-time motion planning and navigation systems that empower our humanoid robots to operate robustly and autonomously in complex logistics and manufacturing environments. This is a high-impact role essential to scaling our commercial deployments, improving the efficiency of autonomous loco-manipulation behaviors, and achieving software readiness for the next generation robot platforms.
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About The Work
<ul>
<li style="font-size: 10pt;">Design, implement, and deploy 3D motion planning algorithms for locomotion, with an emphasis on whole-body collision-aware motion execution in real-time.</li>
<li style="font-size: 10pt;">Own the core components of our navigation stack, specifically the local planning maps, terrain models, and grid map representations used for path and motion planning with collision avoidance.</li>
<li style="font-size: 10pt;">Advance our locomotion capabilities by developing and maintaining a 3D footstep path planner aiming to significantly reduce navigation cycle times.</li>
<li style="font-size: 10pt;">Define and implement the necessary navigation features and route planning algorithms to enable coordinated movement and resource sharing within multi-agent robot fleets.</li>
<li style="font-size: 10pt;">Drive the maturity of our release processes by designing, implementing, and maintaining robust regression testing pipelines for motion planning and navigation modules.</li>
<li style="font-size: 10pt;">Collaborate with the AI and Controls teams to integrate locomotion behaviors with RL policies and support whole-body control.</li>
<li style="font-size: 10pt;">Integrate and debug planning algorithms on real-world hardware, owning the transition from simulation environments (e.g., Gazebo, MuJoCo, Isaac Sim) to physical robots.</li>
</ul>
About You
<ul>
<li style="font-size: 10pt;">5+ years of professional experience in robotics, specifically developing and deploying real-time navigation and motion planning systems for autonomous mobile platforms (humanoids, quadrupeds, autonomous vehicles).</li>
<li style="font-size: 10pt;">Expertise in 3D/volumetric map representations (e.g., octomaps, voxel grids) for local path planning and collision avoidance.</li>
<li style="font-size: 10pt;">Deep technical understanding of locomotion-specific path and motion planning algorithms, including sampling-based planners (RRT/PRM), optimization-based methods (MPC/LQR), and hybrid A*.</li>
<li style="font-size: 10pt;">Expert proficiency in modern C++ (C++17/20), with a proven track record of writing high-performance, multithreaded code for robotics applications.</li>
<li style="font-size: 10pt;">Experience with common robotics frameworks (e.g., ROS/ROS2, DDS) and hands-on experience with modern optimization libraries relevant to motion planning (e.g., Ceres, IPOPT, OSQP).</li>
<li style="font-size: 10pt;">Proven ability to systematically test and debug systems on physical robots, and integrate perceived environment data (LiDAR, camera, depth sensing) into the planner.</li>
</ul>
Bonus Qualifications
<ul>
<li style="font-size: 10pt;">Experience training and deploying Reinforcement Learning (RL) agents for complex locomotion behaviors.</li>
<li style="font-size: 10pt;">Hands-on experience implementing Model Predictive Control (MPC) or similar optimization-based control techniques for dynamic robot locomotion.</li>
<li style="font-size: 10pt;">Familiarity with perception pipelines and the integration of perceived environment data into the planning stack.</li>
<li style="font-size: 10pt;">Experience with GPU-accelerated spatial data structures (e.g., NVBlox, specialized CUDA implementations) for high-throughput, low-latency map updates and querying.</li>
<li style="font-size: 10pt;">Strong foundational knowledge of robot kinematics, dynamics, controls, and state estimation (e.g., EKF, particle filters).</li>
<li style="font-size: 10pt;">Experience with multi-robot coordination/route planning and abiding by boundary constraints in a workcell map.</li>
<li style="font-size: 10pt;">Experience with multi-robot mapping and localization, including map persistence and sharing capabilities.</li>
<li style="font-size: 10pt;">Publications in top-tier robotics conferences (ICRA, RSS, IROS, CoRL).</li>
</ul>
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This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.
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The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.<div class="content-pay-transparency"><div class="pay-input"><div class="title">Anticipated Salary Range</div><div class="pay-range">$155,000&mdash;$241,000 USD</div></div></div><div class="content-conclusion">In addition to base pay, our competitive total rewards package consists of the following for full-time employees:
<ul>
<li>401(k) Plan:&nbsp;Includes a 6% company match.</li>
<li>Equity:&nbsp;Company stock options.</li>
<li>Insurance Coverage:&nbsp;100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.</li>
<li>Benefit Start Date:&nbsp;Eligible for benefits on your first day of employment.</li>
<li>Well-Being Support:&nbsp;Employee Assistance Program (EAP).</li>
<li>Time Off:
<ul>
<li>Exempt Employees:&nbsp;Flexible, unlimited PTO and 10 company holidays, including a winter shutdown.</li>
<li>Non-Exempt Employees:&nbsp;10 vacation days, paid sick leave, and 10 company holidays, including a winter shutdown, annually.</li>
</ul>
</li>
<li>On-Site Perks:&nbsp;Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.</li>
<li>Parental Leave:&nbsp;Generous paid parental leave programs.</li>
<li>Work Environment:&nbsp;A culture that supports flexible work arrangements.</li>
<li>Growth Opportunities:&nbsp;Professional development and tuition reimbursement programs.</li>
<li>Relocation Assistance:&nbsp;Provided for eligible roles.</li>
<li>Annual Discretionary Bonus: Provided for eligible roles.</li>
</ul>
All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.
Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.
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Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies.&nbsp; We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page.&nbsp; If you are represented by a third party, your application may not be considered.&nbsp; To ensure full consideration, please apply directly.
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Apply Now: <a href="https://grnh.se/b444bbd04us" target="_blank">https://grnh.se/b444bbd04us</a></div>

Senior Software Engineer, Navigation 

5+ years in robotics; expertise in 3D/volumetric maps; strong C++ and ROS/ROS2 experience; experience with motion planning, planning stacks, and testing on real hardware.

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