Senior/Algorithms Engineer
Listed on 2026-07-08
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Software Development
Software Engineer, Robotics, AI Engineer (Applied/Software), Machine Learning/ ML Engineer
As a Senior/Staff Algorithms Engineer, you will be working on a myriad of challenges related to robot task and action planning. You will leverage techniques from machine learning, search, discrete and continuous optimization to solve hard sequential decision problems that require reasoning about the physical world and its dynamics. You will also stay abreast of the latest progress in reinforcement learning, task and motion planning, and other related fields in order to further develop Dexterity’s technology foundations in physical AI.
Dexterity’s robotic solutions integrate data from a multitude of sensors, including RGB cameras, depth sensors, force‑torque sensors, encoders, system telemetry and human input. To better inform the planning algorithms, you may work on sensor fusion and state‑estimation techniques to leverage this multimodal sensory data.
You will also work closely with the data platform, physics simulation, and robot operations teams to develop effective and efficient ways to improve the system’s internal world model.
Dexterity has an expanding set of algorithmic challenges as we deploy new robotic applications, including ways to improve packing algorithms to build taller, denser, and more stable structures with a wider variety of objects, solving the logistics task of moving and sorting inventory throughout a warehouse, and building models that understand physics and geometry for both short- and long‑horizon tasks.
In addition to core algorithmic developments, you will be responsible for building high quality, maintainable, and performant software. Ideally, you will bring strong software system design sensibilities and help guide software development within the team more broadly.
Day to Day Activities- Make both revolutionary and evolutionary modifications to various algorithms spanning from modern optimal control to Go solvers
- Collaborate with roboticists, machine‑learning engineers, mechanical engineers, and product managers to find optimal system solutions
- Implement, test, and maintain high quality software
- Develop and maintain accurate models of robotics systems
- Integrate algorithms with existing software infrastructure, including the development of any necessary auxiliary software
- Lead efforts to improve the rigor and performance of algorithms within Dexterity
- Degree in Computer Science, Electrical Engineering, or Mathematics and strong knowledge of Modern C++ and Python (preferred)
- 5+ years of relevant Industry or Research experience
- Familiarity with Linux and git versioning
- Experience with Optimization (convex, continuous, combinatorial, etc.)
- Experience with various Search Strategies such as Monte Carlo Tree Search (MCTS), Depth‑First Search (DFS), etc.
- Knowledge of Constraint Satisfaction Problems, Statistics and State Estimation
- Experience in System Modeling, Task and Motion Planning
- Experience with Docker and Kubernetes
- Previous startup experience
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Salary170,000 – 225,000 USD a year
Our Total Rewards philosophy is designed to recognize contributions toward meaningful innovation. Base pay is one component of a broader compensation package that may include equity grants, benefits, and other incentives, depending on role and eligibility.
For this position, the expected base salary range is $170,000 to $225,000 annually. Actual compensation will be determined based on skills, experience, education, and market factors, and may vary accordingly.
Final compensation decisions are made individually and take a number of factors into consideration. Eligible employees may be considered for equity awards as part of their overall compensation. Access to benefits and wellness resources is provided in accordance with company policies and may vary based on role and location.
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