Embedded Engineering Manager - Robotics & Drones

• Lead engineering teams responsible for:
• Embedded systems architecture and platform software.
• Sensor integration and data acquisition (cameras, lidar, radar, depth sensors, IMUs, and related technologies).
• Sensor data ingestion, preprocessing, synchronization, and transport.
• Runtime inference, diagnostics, monitoring, and health management.
• System-level integration across perception, localization, planning, safety, and control subsystems.
• Establish engineering standards, architecture guidelines, and software development best practices that support scalable, production-ready robotics systems.
• Drive technical execution from concept through deployment while ensuring reuse across multiple robot and autonomous platform form factors.

• Resolve critical technical escalations and remove engineering roadblocks by working directly with product teams when necessary.
• Support product development teams throughout the development lifecycle, ensuring technical risks are identified and mitigated early.
• Drive cross-functional problem solving across hardware, software, autonomy, safety, and product organizations.
• Partner with Technical Program Managers and engineering leads to balance priorities, schedules, resources, and technical scope.
• Drive continuous process, methodology, and workflow improvements to improve engineering quality, predictability, and efficiency.

• Directly manage and grow multiple systems, software, and perception engineering teams.
• Establish clear goals, expectations, priorities, and performance objectives aligned with product and organizational strategies.
• Lead hiring, onboarding, performance management, succession planning, and career development activities.
• Mentor engineers and technical leaders in:
• Systems architecture and embedded software design.
• Robotics and autonomous system development.
• Scalable software engineering and DevOps practices.
• Root-cause analysis, problem solving, and technical decision making.
• Foster a culture of ownership, quality, innovation, collaboration, and continuous learning.
• Identify future staffing, skillset, and resource needs based on product roadmaps and organizational growth plans.

• Partner closely with hardware, SoC, and platform engineering teams to:
• Evaluate and select sensors, compute platforms, and acceleration technologies.
• Define system architectures that balance performance, power consumption, cost, and scalability.
• Ensure robust timing, synchronization, communication, and bandwidth management.
• Collaborate with autonomy, localization, planning, controls, and safety teams to establish system interfaces, requirements, data contracts, diagnostics, and performance expectations.
• Support build-versus-buy evaluations for sensors, software frameworks, perception technologies, SDKs, and third-party components.
• Work closely with Product Managers, Technical Program Managers, and customers to translate business and operational requirements into technical solutions.

• Define and track system and perception performance KPIs including reliability, latency, availability, robustness, scalability, confidence calibration, and operational performance.
• Ensure systems perform reliably in challenging real-world operating environments, including dynamic obstacles, environmental variability, sensor degradation, and adverse conditions.
• Partner with safety engineering teams to identify hazards, analyze failure modes, and support FMEA, fault injection testing, and degraded-mode operations.
• Establish monitoring, diagnostics, observability, and health assessment strategies to ensure safe and reliable operation.
• Drive continuous improvement through field data analysis, root-cause investigations, corrective actions, and iterative product enhancements.

• Engage with customers, partners, and industry stakeholders to understand use cases, operational requirements, and emerging market needs.
• Support pilots, demonstrations, proof-of-concept activities, and customer escalations.
• Communicate technical capabilities, limitations, risks, and trade-offs clearly to both technical and non-technical audiences.
• Incorporate customer feedback and field learnings into product strategy, roadmap planning, and engineering priorities.

• Bachelor’s or Master’s degree in Computer Science, Electrical/Computer Engineering, Systems Engineering, or a related technical field.
• 10+ years of experience developing embedded systems for robotics, automotive, consumer electronics, or related products.
• 3+ years of engineering leadership and people management experience leading systems and software development teams.
• Proven experience managing, mentoring, and developing high-performing engineering organizations.
• Strong technical expertise in systems engineering, embedded software, and product development best practices.
• Experience leading cross-functional development across hardware, software, systems, safety, and product management teams.
• Strong understanding of system architecture, sensor integration, and software platforms.
• Proven ability to drive end-to-end ownership, technical execution, roadmap planning, and team accountability.
• Demonstrated success resolving complex technical challenges and delivering products on schedule and at scale.
• Strong communication, collaboration, and stakeholder management skills.
• Experience building engineering roadmaps, resource plans, and organizational capabilities aligned with business objectives.
• Track record of fostering a culture of engineering excellence, continuous improvement, accountability, and talent development.

• Experience with robotics software frameworks and middleware, including ROS and ROS 2.
• Familiarity with modern software development methodologies, including Agile, CI/CD, automated testing, and DevOps practices.
• Working knowledge of perception, sensor processing, computer vision, and machine learning technologies used in autonomous systems.
• Experience deploying and managing ML-based perception systems in production environments, including safety-relevant or human-adjacent applications.
• Experience optimizing software and ML inference workloads on embedded compute platforms, GPUs, NPUs, DSPs, or other hardware accelerators under real-time constraints.
• Experience with system architecture, systems engineering, requirements analysis, and Model-Based Systems Engineering (MBSE).
• Familiarity with industry standards and processes such as Automotive SPICE, ISO 26262, functional safety, and robotics safety-critical system development.
• Experience with cybersecurity principles and secure embedded system design, including encryption, TLS, wireless communication security, and network protection mechanisms.
• Familiarity with microprocessor- and DSP-based hardware architectures, embedded software platforms, and hardware/software integration.
• Experience with embedded communication interfaces and protocols.
• Experience with requirements management processes and tools such as Polarion, DOORS, or equivalent platforms.
• Proven track record of translating customer requirements into production-ready products and engineering solutions.
• Experience working in startup, incubation, or high-growth environments requiring strong ownership, adaptability, and comfort operating in ambiguity.

Traits we seek:

• Curiosity-driven problem solvers who investigate deeply and think systemically.
• Confident leaders who empower teams, set direction, and earn trust.
• Hands-on learners with an experimental, builder mindset.
• Resilient thinkers who see challenges as opportunities to learn and improve.

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