Engineering Manager, Perception and Machine Learning

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Engineering Manager, Perception and Machine Learning based in the United States. This role leads the engineering team responsible for building perception and machine learning capabilities that enable autonomous systems to understand and respond to complex real-world environments. You’ll combine technical leadership with people management, guiding a multidisciplinary team across perception, ML, sensor fusion, and software engineering. The role spans the full development lifecycle, from research and data curation through evaluation, testing, deployment, and field readiness. You’ll work closely with autonomy, embedded, data, simulation, hardware, product, programs, and field teams to translate mission requirements into practical engineering priorities. Real-world performance, reliability, compute constraints, and operational feedback will shape how you prioritize and mature the technology. This is an opportunity to build a high-performing engineering organization while contributing to advanced autonomous systems operating across challenging environments.

Lead, manage, mentor, and develop a team of perception, machine learning, sensor fusion, and software engineers. Own team planning, prioritization, execution, and delivery against the Perception and Machine Learning roadmap. Establish clear goals, responsibilities, expectations, and accountability across the engineering team. Partner with senior technical contributors to guide architecture and technical decisions across computer vision, sensor fusion, tracking, detection, classification, segmentation, and related capabilities. Oversee the development and maturation of model training, evaluation, data curation, validation, and deployment workflows. Ensure perception systems are designed for real-world performance, reliability, compute constraints, and field readiness. Translate customer, mission, and product requirements into clear engineering priorities, roadmaps, and execution plans. Partner cross-functionally with Autonomy, Embedded, Data, Simulation, Hardware, Product, Programs, and Field Operations teams. Use field data, testing results, and operator feedback to identify performance gaps and prioritize technical improvements. Establish strong engineering practices around design reviews, code reviews, testing, model evaluation, release readiness, and technical documentation. Identify execution risks, dependencies, resource constraints, and technical tradeoffs, communicating them clearly to engineering leadership and stakeholders. Balance technical performance, delivery timelines, resources, risk, and product requirements when making engineering decisions. Coach engineers through regular feedback, performance management, career development, and technical mentorship. Recruit, interview, onboard, and retain high-performing engineering talent as the organization grows. Foster a culture of technical excellence, ownership, collaboration, innovation, and continuous improvement. Requirements: Bachelor’s degree in Computer Science, Machine Learning, Robotics, Electrical Engineering, Computer Engineering, or a related technical field. 7+ years of relevant engineering experience in perception, machine learning, computer vision, robotics, autonomy, sensor fusion, or related disciplines. 2+ years of direct people-management experience, ideally leading engineers in a highly technical environment. Strong technical understanding of modern perception systems, including computer vision, sensor fusion, tracking, detection, classification, and ML-based scene understanding. Experience taking machine learning or perception capabilities from development through testing and deployment in real-world systems. Demonstrated ability to manage engineering priorities, technical roadmaps, dependencies, and delivery across multiple initiatives. Experience hiring, coaching, developing, and evaluating engineering talent. Strong cross-functional leadership experience working with software, autonomy, data, hardware, product, and field teams. Ability to make sound decisions across technical performance, schedules, resources, risks, and product requirements. Excellent communication skills, with the ability to explain complex technical issues and tradeoffs to both technical and non-technical stakeholders. High ownership, sound judgment, and the ability to operate effectively in fast-moving and ambiguous environments. U.S. citizenship and the ability to obtain and maintain a security clearance. Advanced degree in a relevant technical discipline is preferred. Previous management experience within Perception, ML, Robotics, or Autonomy teams is preferred. Experience with robotics, autonomous vehicles, defense technology, aerospace, maritime systems, or other deployed autonomous systems is a plus. Familiarity with multimodal sensor systems such as cameras, EO/IR, radar, LiDAR, AIS, GPS/INS, or IMU is preferred. Experience with technologies such as PyTorch, TensorRT, ONNX, CUDA, MLflow, Docker, Kubernetes, NVIDIA Jetson, or similar ML and deployment platforms is advantageous. Experience with simulation, synthetic data, annotation workflows, and large-scale perception datasets is a plus. Experience supporting field testing, customer demonstrations, operational evaluations, or deployed robotic systems is preferred. Government or DoD program experience and an active or prior security clearance are advantageous. Benefits: $200,000–$225,000 annual salary. Equity package. Bonus opportunity. 100% employer-paid health, dental, and vision insurance for employees and families. Employer-paid life insurance. 401(k) program with company matching. Unlimited PTO with a two-week minimum. Work-from-home and home office stipend. 16 weeks of paid parental leave. Monthly health and wellness stipend. Global Entry benefit. Opportunity to lead a highly technical engineering organization working on advanced autonomous systems. Collaborative, mission-driven environment focused on innovation, integrity, ownership, and continuous improvement.

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