Maven Robotics, Inc.

A robotics company in San Francisco seeking a Machine Learning Engineer to design and deploy algorithms enhancing robot perception. Responsibilities include developing ML-based algorithms for object detection and integrating sensor fusion techniques. Ideal candidates hold an MS or PhD in relevant fields and possess strong skills in computer vision, deep learning, and Python/C++. This is an exciting opportunity in a fast-paced startup environment.

Location Role Description We are looking to recruit an exceptional Machine Learning Engineer - Robot Perception to design, implement, test, and deploy robot perception algorithms that power our robots' ability to understand and interact with the world. Responsibilities Develop, train, and deploy ML-based perception algorithms for object detection, pose estimation, tracking, and scene understanding. Integrate sensor fusion techniques using cameras, depth sensors, IMUs, and tactile feedback. Optimize real-time perception pipelines for low-latency and robust performance in dynamic environments. Work closely with hardware engineers to design sensor configurations and optimize perception models for onboard deployment. Contribute to our broader AI and autonomy stack, ensuring seamless integration with reasoning, manipulation, planning and control. Collaborate across disciplines to ensure seamless integration of ML models and provide technical mentorship to junior engineers. Qualifications Must-have MS or PhD in machine learning, computer science, robotics, or a related field. Strong background in computer vision, deep learning, and sensor fusion. Proficiency in Python and C++, with experience in frameworks like PyTorch, TensorFlow, OpenCV, and ROS. Hands on experience with real world robotics perception systems (e.g., SLAM, 3D reconstruction, multimodal perception). Experience working with hardware, including setting up and calibrating cameras, LiDAR, and other sensors. Experience with data collection, preprocessing, and management in the context of training ML models. Self starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions. Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics. Nice-to-have Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim to real transfer. Experience in: Developing models that can handle noisy, incomplete, or sparse data. Deployment of ML models to edge devices for real time inference (e.g., NVIDIA Jetson). Accelerating ML training processes using GPU, TPU, or other HW accelerators. General knowledge of robotics principles, including kinematics, dynamics, and control.

Embedded Software Engineer - Real-Time Embedded LOCATION: Role Description We are looking to recruit an exceptional Embedded Software Engineer - Real-Time Embedded to develop the foundational software that keeps our robot hardware alive, building the core systems that provide a platform for robust, safe, and deterministic operation. Responsibilities Adapt and integrate a safety certifiable Real Time Operating System (RTOS) and associated drivers for purpose built robotic control hardware. Collaborate with hardware engineers to design, develop, and optimize high performance safety-critical systems. Develop and adapt device drivers for hardware peripherals (e.g. GPIO, EtherCAT, SPI). Build tools to monitor, verify and optimize real time system performance, ensuring deterministic behavior. Contribute to a deterministic and reproducible build and test environment for efficient development. Collaborate with functional safety engineers to ensure compliance with relevant safety standards and support audit and traceability requirements. Develop robust solutions for over-the-air (OTA) updates, calibration management and software deployment strategies. Solve complex, real-world challenges alongside a multi-disciplinary team Qualifications Must-have MS in computer engineering, computer science or a related discipline. Experience with safety-certifiable RTOSes (e.g. PX5, ThreadX, SafeRTOS). Expertise in OS fundamentals, including real-time scheduling and memory management. Strong understanding of ARM 64 hardware architecture. Experience with multicore SoCs, interprocess/intercore communications and atomic operations. Production experience with communication protocols (e.g. Ethernet, EtherCAT, CAN) Proficiency in low level programming (C, assembly) Understanding of bootloaders, hardware abstraction layers and board support packages (BSPs). Hands on experience with development tools including oscilloscopes, hardware debuggers and high speed tracing techniques (e.g. HSSTP). Understanding of toolchains (compilers, linkers, debuggers, static analysis tools) Familiarity with functional safety (FuSa) concepts, MISRA compliance, and related standards. Self starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions. Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics. Nice-to-have Knowledge of ARM SIMD/NEON architecture extensions. Proficiency in additional programming languages (e.g. C++, Python, Rust, Golang). Experience with multi language build systems (e.g. Bazel, Bob). Familiarity with ROS 2 middleware and alternatives (e.g. FastDDS, CycloneDDS, Zenoh). Experience with Docker, and related containerization tools.

A robotics company in San Francisco is searching for an Electrical Engineer specializing in Compute Hardware Design. The ideal candidate will have a Bachelor's or Master's degree in electrical engineering and at least 5 years of relevant experience. You'll design and test innovative hardware as part of a cross-functional team. Key qualifications include expertise in circuit design and PCB layout, with proficiency in tools like Altium Designer.

Overview We are looking to recruit an exceptional Software Engineer - Software Development and Machine Learning Operations to build and maintain the infrastructure that supports our software development, machine learning models, and AI operations. Responsibilities Design, implement, and manage CI/CD pipelines to facilitate seamless code integration and deployment. Monitor and optimize system performance, availability, and security. Automate infrastructure orchestration and configuration management using tools such as Kubernetes, Ansible, and similar. Configure and maintain data infrastructure appliances. Troubleshoot and resolve issues related to applications, infrastructure, and deployments. Work closely with our development and AI teams to deliver solutions that increase efficiency and stability. Qualifications Must-have: BS or MS in software engineering, computer science, or a related field. Proven experience standing up a CI/CD system from scratch. Experience with multi-language build systems (e.g., Bazel, Bob). Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience with automation tools (e.g., Terraform, Ansible, GitHub Actions, Jenkins) and version control systems (e.g., Git). Strong programming skills in languages such as Python, Go, or Java. Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions. Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics. Nice-to-have Experience with MLOps platforms (e.g., MLflow, Kubeflow, or SageMaker). Knowledge of big data technologies (e.g., Hadoop, Spark, or Kafka). Experience with monitoring and observability tools (e.g., Prometheus, Grafana, ELK stack). Understanding of machine learning frameworks (e.g., TensorFlow, PyTorch, or Scikit-Learn). Experience with edge computing and IoT device management. Knowledge of security best practices and compliance standards in AI/ML environments. Proficiency in database management systems (e.g., PostgreSQL, MongoDB, or Cassandra). Experience with infrastructure-as-code tools (e.g., CloudFormation, Pulumi). Knowledge of GitOps practices and tools (e.g., ArgoCD, Flux).