Machine Learning Ops (ML Ops) Technical Fellow

Key Skills

Argo, Containerization, Continuous Integration & Continuous Delivery - CI/CD, CUDA/GPU programming, Docker, Effective communication skills, Kubeflow, Kubernetes-K8s, Machine learning techniques, MLflow, MLOps tools, PyTorch, Ray.io, Scikit-learn, SPARK Programming, TensorFlow

Job Description

This position does not require an employee to be on-site full-time to perform most effectively. The employee’s role enables them to work at a GM facility or off-site as frequently as needed or desired. Relocation may be provided. This position requires employee to be onsite 1-3x per week.

GM Digital Business Team Technology (DBTT) is a dynamic and fast paced organization that designs, develops, and maintains all applications and solutions that create the entire interactive experience for customers and vehicles at General Motors. From designing and building the next generation of electric and other vehicles to developing a world-class GM experience for our dealers and customers, DBTT is driving real change in the most iconic automaker on the planet. Our team delivers unique enterprise-wide IT solutions in cutting-edge technologies such as mobility, telematics, mission-critical business systems, supercomputing, cloud, vehicle engineering and real-time computing. We offer challenging positions for passionate professionals looking to advance their careers and be a part of an organization focused on innovation, speed, and business value.

GM DBTT is looking for a dynamic, experienced Machine Learning Ops (ML Ops) Technical Fellow to design and lead the vision of the ML Ops pipeline that will support Artificial Intelligence and Machine Learning (AI/ML) products and services. The Machine Learning Ops Technical Fellow will be responsible for driving technical direction and leadership for the development and operation of efficient ML pipelines that will support the business, research, and IT users in developing ML models. The focus will be driving external teams to implement service-based API architectures designed for the Mobile experience. This role will be responsible for help guide enterprise-wide strategic decision-making related to ML Ops. 

Additional Description

Major Duties/Responsibilities

As a key leader in the organization, you will be responsible for overseeing engineering work across a suite of technologies within the broader AI/ML space at GM.

Recognition within the Field

The ML Ops Technical Fellow will be expected to be a recognized expert within the AI/ML field, both internally and beyond GM. This includes but is not limited to:

• Authoring cited work in refereed journal publications and conference proceedings
• Holding leadership positions in professional organizations, industry committees or task forces
• Delivered professional speeches given in area of expertise internal or external to GM
• Taught and/or developed courses in area of expertise internal or external to GM

Thought Leadership

The fellow is expected to provide thought leadership to help drive the AI/ML organization. Expected activities include:

• Provide technical guidance to senior leadership team on strategy for achieving product goals with an emphasis on pursuing work and decisions that provide value to multiple products.
• Provide technical and architectural guidance/direction for scientists to maximize value of work across all products.
• Continued deep engagement with latest developments in the technical stack for ML.
• Contribute to setting future technical strategy/vision for GM ML Ops
• Identify new potential products, proof of concept development, and engagement with business stakeholders on such initiatives.
• Advise senior leadership on process/products that have a readily recognizable short to mid-term impact on the organization.

Core Responsibilities

• Design, build, and maintain the core machine learning capabilities, services and platforms used by General Motors’ autonomous vehicle development and data science teams.
• Lead teams and projects designing and deploying General Motors’ ML Ops infrastructure
• Assist and guide teams deploying ML products and services and leveraging new ML tools
• Provide strategic vision and long-term planning for General Motors’ ML Ops architectures and tooling to enable continuous capability expansion
• Implement components of ML-enabled applications at-scale in a distributed computing environment.
• Drive testing, releases, and monitoring of machine learning based products on the platform.
• Write high quality, shippable code across the stack that is easy to maintain and test.
• Collaborate with ML scientists, machine learning engineers, and product teams to define high impact product features and deliver them with quality.
• Scrutinize and clearly communicate the technology and architecture choices we make.
• Implement integrated monitoring of model performance for reliability and maintenance.
• Continuously improve ML processes, tools and standards.

Required Qualifications

• 15+ years of software development and/ or architect-infrastructure engineering experience.
• Proven track record and experience in orchestrating Machine Learning solutions to production at scale.
• Proven track record of thought leadership. Experience of ML practice development in a large ML based product development organization is a plus
• Should be able to handle multiple ML initiatives simultaneously and lead/mentor a team of engineers
• Applied background in machine learning platform development, software development, CI/CD and deployment patterns.
• Experience with Data and ML Orchestration, Containerization, and GPU Compute technologies such as Docker, Spark, Kubernetes, and CUDA.
• Experience with ML software technologies such as Pytorch, Tensorflow, Ray or sklearn.
• Experience with workflow tracking and visualization technologies like ARGO, KubeFlow, MLFlow, TensorBoard, etc.
• Strong Candidates will be knowledgeable in Data and ML Engineering with both on-prem and cloud infrastructure
• Experience leading high-impact, cross-company initiatives
• Excellent communication skills in presentation (both verbal and slides)

COMPENSATION

The median level of salary compensation for this role is

• $154,828 - $195,985

BONUS POTENTIAL

An incentive pay program offers payouts based on company performance, job level, and individual performance. 

BENEFITS

GM offers a variety of health and well-being 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.