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Goddard

Medical devices and robotics product development

Senior Software Engineer - Robotics & Physical AI Integration

Robotics & Autonomous SystemsUpdated on Nov 15
Full-timeWilmington, MA, USAIn-person

About the Job

Requirements

  • At least 5 years of systems or robotics software engineering experience, including a demonstrated track record of shipping software that controls physical hardware in production.
  • Strong proficiency in C and C++; Python proficiency for tooling, scripting, and test automation.
  • Hands-on experience writing ROS or ROS 2 nodes, services, actions, and hardware interface layers; familiarity with launch systems, parameter management, and tf2.
  • Hands-on experience interfacing with industrial robot controllers from one or more major vendors or equivalent; working knowledge of robot coordinate frames, kinematics, end-of-arm tooling interfaces, teach pendant workflows, and vendor-specific programming environments such as Karel, KRL, RAPID, or URScript.
  • Practical experience implementing at least one industrial fieldbus protocol—EtherCAT, CANopen, Modbus, or Profinet—in a production system.
  • Working knowledge of SPI, I2C, UART, CAN, and GPIO, and experience debugging communication failures at the signal level.
  • Experience with real-time Linux (PREEMPT_RT or Xenomai) or an RTOS (FreeRTOS, Zephyr, or QNX) for deterministic control, including understanding how to measure and bound latency.
  • Familiarity with functional safety standards relevant to machinery or software in safety-critical systems, such as IEC 62304, ISO 13849, or IEC 61508, and ability to translate safety requirements into software constraints.
  • Ability to isolate failures in systems where root causes may be in software, firmware, hardware, or the interfaces between them.
  • Solid software engineering fundamentals, including Git, code review, unit and integration testing, and CI/CD, applied to systems code.
  • Bachelor's degree in Computer Science, Electrical Engineering, Robotics, Mechatronics, or a related field.

Responsibilities

  • Design and implement software integrating machine-learning model inference outputs with physical hardware, including motion controllers, servo drives, actuators, and industrial I/O.
  • Develop and maintain ROS 2 nodes, hardware abstraction layers, and device drivers for robotics and automation hardware; implement and own communication stacks across industrial fieldbuses including EtherCAT, CANopen, Modbus, and Profinet.
  • Interface with industrial robot controllers through vendor SDKs, proprietary communication interfaces, and standard industrial protocols; translate controller capabilities and constraints into software integration requirements.
  • Interface with low-level embedded hardware over SPI, I2C, UART, GPIO, and CAN, and collaborate with embedded engineers to define cross-boundary interfaces.
  • Integrate machine vision and camera systems, including image acquisition pipelines, sensor calibration, and routing vision outputs to downstream control and inference logic.
  • Collaborate with the ML Engineer to define inference APIs, data contracts, and performance budgets between model outputs and physical actuators.
  • Develop real-time and near-real-time control loops on Linux (PREEMPT_RT) and RTOS targets, accounting for scheduling, jitter, and determinism requirements.
  • Build hardware-in-the-loop and integration test infrastructure to verify system behavior with and without live hardware.
  • Document software architecture, interface contracts, timing assumptions, and integration procedures for internal engineering and regulatory purposes.
  • Identify integration risks, timing failures, and hardware/software boundary issues before they become field problems.

Desired Qualifications

  • Experience integrating machine vision systems using GigE Vision, USB3 Vision, or similar standards; familiarity with OpenCV or other vision processing libraries.
  • Working knowledge of motion control concepts, including servo tuning, trajectory generation, path planning, and force/torque sensing and control.
  • Experience consuming ML inference runtimes such as TFLite, ONNX, or TensorRT within a control or perception pipeline, and understanding of their operational constraints.
  • Exposure to simulation and digital twin environments such as Gazebo, NVIDIA Isaac Sim, or MoveIt for offline testing and development.
  • Experience in a startup or small-team environment, owning architecture decisions and building tooling and process alongside the product.
  • An advanced degree is a plus, but does not substitute for hands-on experience shipping software that controls physical systems.

About the Company

Goddard

Medical devices and robotics product development

Goddard Technologies is a bi-coastal, full-service product development consultancy that helps create medical devices, industrial automation systems, and robotic technologies. It combines engineers, designers, and project managers to guide projects from concept to reality. The company offers two service options: ACE (Advanced Collaborative Engineering) and Product Development, both designed to tailor the work to a client’s needs and to provide hands-on collaboration throughout the process. Unlike firms that focus on a single stage, Goddard stays involved across the development cycle, from initial ideas through testing and deployment, with emphasis on practical execution and client support. The goal is to deliver clear, practical support and outcomes that help clients bring safe and effective products to market.”} वाप нonsense to=functions.final_result retten ῶ? } {

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Lower Merion Township, Pennsylvania
Founded
1997

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