• Design, build, and deliver machine learning models and pipelines in close collaboration with Data Science, Research, and Engineering teams. • Own and evolve complex ML systems, ensuring they remain scalable, reliable, and maintainable in production. • Drive technical excellence and best practices across the entire ML lifecycle, from modeling and evaluation to deployment and monitoring. • Define and implement production standards that increase the quality and speed of development across the Data & ML organization. • Translate complex business problems into robust ML solutions with measurable and durable impact on product outcomes. • Act as a technical leader and mentor, supporting the growth of ML practices and elevating the skills of less experienced team members

Job Description At General Motors, our product teams are redefining mobility. Through a human-centered design process, we create vehicles and experiences that are designed not just to be seen, but to be felt. We’re turning today’s impossible into tomorrow’s standard —from breakthrough hardware and battery systems to intuitive design, intelligent software, and next-generation safety and entertainment features. Every day, our products move millions of people as we aim to make driving safer, smarter, and more connected, shaping the future of transportation on a global scale. Role As a Senior Machine Learning Engineer for Perception within the Embodied AI organization, you will own the end-to-end pipeline for safety-critical ML perception models, from initial research and large-scale data curation to optimization and real-time deployment on the vehicle's compute platform. Your primary mission is to enable the vehicle to accurately and reliably see, classify, and track everything in its environment—from rare road markings and complex intersections to vulnerable road users (VRUs). Responsibilities ​ - End-to-End Model Lifecycle: Own the design, training, validation, and deployment of deep learning models for core perception tasks such as: - 3D Object Detection and Tracking (vehicles, pedestrians, cyclists). - Real-time map detection of the drivable world (lanes, road boundaries, traffic signs). - Multi-Modal Sensor Fusion (Camera, LiDAR, Radar). - Production Pipeline: Build and scale the ML training infrastructure, including data mining and loading, multi-stage training and evaluation, to streamline model development. - Performance Optimization: Improve model performance through data iterations, parameter tunings, training strategy and architecture updates to produce reliable models that meet and the strict real-time, low-latency requirements on the vehicle's embedded hardware. - Model Debugging: Conduct rigorous, data-driven analysis to identify, debug, and resolve performance degradations and failures, specifically targeting long-tail and adversarial scenarios (e.g., adverse weather, sensor noise, occlusions). - Metric Definition: Define and implement robust model-level metrics to aid model development. - System Integration: Work closely with the Safety, Systems, and other engineering functions to integrate Perception outputs. Skills & Experience ​ - BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field. - 5+ years of professional experience with a focus on Computer Vision, Deep Learning, and Perception in a production environment. - Deep hands-on experience with modern deep learning frameworks (e.g., PyTorch or TensorFlow) for training, experimentation, and debugging complex DNNs. - Proven experience working with and fusing data from multiple sensor modalities (Camera, LiDAR, and/or Radar). - Practical experience deploying and optimizing ML models for resource-constrained, real-time embedded systems. - Demonstrated ability to drive model improvements through large-scale data analysis, error logging, and data curation. Bonus: - Expertise with Transformer-based models for 3D detection, tracking, and scene understanding. - Technical leadership experience, including mentoring junior engineers and leading major feature development from concept to launch. - Contributions to relevant academic publications (CVPR, ECCV, ICCV, IROS, NeurIPS etc.). Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times per week, at minimum. Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of the California Bay Area. - The salary range for this role is $170,600.00 to $261,300.00. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. - Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: - Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more. This job may be eligible for relocation benefits. #GM-AV-1 About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

• Design, prototype, implement, evaluate, optimize systems to generate sports datasets and predictions with high accuracy and low latency. • Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow. • Build, test, deploy and maintain production systems. • Work closely with DevOps and Data Engineering teams to assist with implementation, optimization and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages. • Support maintenance and optimization of cloud-native EDW and ETL solutions. • Maintain and promote best practices for software development, including deployment process, documentation, and coding standards. • Experience applying large scale data processing techniques to develop scalable and innovative sports betting products. • Use extensive experience to build, test, debug, and deploy production-grade components. • Participate in development of database structures that fit into the overall architecture of Swish systems.

• Lead and mentor a high-performing Machine Learning Science team focused on delivering impactful ML/AI solutions that drive business outcomes. • Partner closely with cross-functional engineering and product teams to define, prioritize, and execute high-impact initiatives. • Drive research and development of machine learning models, including semantic search, personalized and real-time recommendations, and agentic learning approaches. • Define and execute a mid- and long-term vision for scalable ML architecture across key domains such as personalization, search, and real-time performance optimization. • Recruit, develop, and retain a diverse team of top-tier scientific talent, elevating the capabilities and influence of The Knot’s Machine Learning Science organization. • Actively contribute to the broader technical community by sharing insights through internal knowledge-sharing sessions, technical documentation, and external publications or blog posts.