Job description

Job Description As a Senior Software Engineer on the SimCore team, you will build and deploy applied AI/ML solutions that directly support simulation workflows, internal tools, and mission-critical engineering use cases. You will operate at the full spectrum of innovation—from early exploration and rapid prototyping to shipping robust, maintainable production systems. You will collaborate closely with simulation, scenario-generation, data, and engineering teams to uncover opportunities where AI can create value —then deliver solutions that meet clear customer and business success criteria. We are looking for a Senior Software Engineer with a strong applied research background. Ideal candidates have hands-on experience with state-of-the-art multimodal GenAI and/or 3D reconstruction models, and excel at building robust, high-performance inference pipelines. This role is not focused on training foundation models, but rather on fine‑tuning, adapting, optimizing, evaluating, and shipping them as production systems. Minimum Qualifications Master’s degree required, PhD preferred, in CS, Robotics, EE, or related fields. 5 years of applied ML/AI engineering experience, with at least 2 years delivering production AI systems at scale. VLM and ML world model building this physical model from. Sensor to sensor, and sensor to 3D. Deep knowledge of at least one modern multimodal or 3D computer vision pipeline (e.g., NeRF, Gaussian Splatting, world models, diffusion-based generation). Strong programming skills in Python, along with experience using a modern ML/AI library such as PyTorch, TensorFlow, OpenAI APIs, HuggingFace, gsplat, etc. Solid understanding of ML fundamentals including data preprocessing, training pipelines, evaluation metrics, and model performance optimization. Ability to move fluidly between research exploration and practical engineering. Demonstrated ability to lead projects end-to-end with minimal guidance. Preferred Qualifications Proven experience fine-tuning and optimizing foundation models (LLMs, VLMs, diffusion, 3D neural models). Experience integrating models into simulation pipelines, robotics systems, mapping workflows, or AV perception stacks. Experience with scene understanding, or computational geometry Background in 3D geometry, graphics, or sensor modeling. Proficiency with vector search/RAG systems and embedding pipelines. Familiarity with GCP or other cloud platforms, Kubernetes, Docker, and production observability. Prior experience mentoring teams, defining architecture, and leading multi-quarter technical initiatives. Compensation: The expected base compensation for this role is: $170,600 - $261,300. Actual base compensation within the identified range will vary based on factors relevant to the position. You also need to include general information about potential commissions, if applicable. 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. 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.

Requirements

Must-haves

5 years of applied ML/AI engineering experience, with at least 2 years delivering production AI systems at scale.
VLM and ML world model building this physical model from. Sensor to sensor, and sensor to 3D.
Deep knowledge of at least one modern multimodal or 3D computer vision pipeline (e.g., NeRF, Gaussian Splatting, world models, diffusion-based generation).
Strong programming skills in Python, along with experience using a modern ML/AI library such as PyTorch, TensorFlow, OpenAI APIs, HuggingFace, gsplat, etc.
Solid understanding of ML fundamentals including data preprocessing, training pipelines, evaluation metrics, and model performance optimization.
Ability to move fluidly between research exploration and practical engineering.
Demonstrated ability to lead projects end-to-end with minimal guidance.

Nice-to-haves

Master’s degree required, PhD preferred, in CS, Robotics, EE, or related fields.
Proven experience fine-tuning and optimizing foundation models (LLMs, VLMs, diffusion, 3D neural models).
Experience integrating models into simulation pipelines, robotics systems, mapping workflows, or AV perception stacks.
Experience with scene understanding, or computational geometry
Background in 3D geometry, graphics, or sensor modeling.
Proficiency with vector search/RAG systems and embedding pipelines.
Familiarity with GCP or other cloud platforms, Kubernetes, Docker, and production observability.
Prior experience mentoring teams, defining architecture, and leading multi-quarter technical initiatives.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlpythongcpkubernetesdocker

Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision