General Motors - Bismarck, ND

posted about 2 months ago

Full-time - Mid Level
Remote - Bismarck, ND
Transportation Equipment Manufacturing

About the position

The Staff Machine Learning Engineer at General Motors will play a pivotal role in driving the vision and execution of LiftIQ, a Marketing Experimentation and Optimization Platform. This position requires a technical leader with expertise in building scalable Machine Learning data products focused on experimentation and optimization. The engineer will be responsible for experiment design, statistical and machine learning models for measurement, optimization, and personalization, leveraging both first-party and third-party data sources. Collaboration with cross-functional teams, including engineering, data science, and UX/UI design, is essential to build and refine the platform that enables effective experimentation, measurement, and optimization. In this role, the Staff ML Engineer will work closely with stakeholders from GM's vehicle brands, subscriptions, and customer care products, as well as the Performance Driven Marketing team. The goal is to ensure business acceptance of models, metrics, and the visualization of experiment performance and optimization. The engineer will develop platforms, tools, and democratized capabilities that empower stakeholders and data scientists to identify marketing initiatives with high return on investment. The team is dedicated to delivering future-focused, consumer-centric, personalized solutions that will help GM remain proactive and agile during the transition to electric vehicles (EVs). The Staff ML Engineer will also be responsible for designing and engineering efficient and resilient ML platforms and software products that can operate at scale. They will participate in design, architecture, and code reviews, fostering collaboration and guiding the team through roadmap deliverables and technical challenges. As a technical leader, the engineer will raise the bar for ML engineering by improving best practices, producing exemplary code, documentation, automated tests, and thorough monitoring. They will possess contextual business knowledge and functional domain expertise in experimentation systems related to marketing, media, customer, digital channels, loyalty, and subscriptions to drive incremental value. Additionally, the engineer will manage stakeholder relationships, prioritize requests, and lead a team capable of tackling diverse business problems while ensuring high-quality delivery across the organization.

Responsibilities

  • Work closely with Data Scientists, Engineers, and Product Owners to optimize ROI for marketing stakeholders.
  • Design and engineer efficient and resilient ML platforms and software products that run at scale.
  • Participate in design, architecture, and code reviews, fostering collaboration and guiding the team through technical challenges.
  • Raise the bar of ML engineering by improving best practices and producing exemplary code and documentation.
  • Possess contextual business knowledge in experimentation systems related to marketing and customer channels.
  • Drive a strategic roadmap with executable outcomes to provide business value and impact.
  • Manage stakeholder relationships and prioritize requests effectively.
  • Lead and develop a team to tackle diverse problems across the business.

Requirements

  • Bachelor's degree in computer science, Data Science, Applied Mathematics, or related quantitative field, or equivalent experience.
  • 5-8+ years of experience in full stack software development, machine learning, data science, or quantitative insights.
  • Strong programming skills in Python and Spark for implementing machine learning algorithms and data pipelines.
  • Proficiency in full stack software development using React and custom visualization using D3.
  • Expertise in diverse machine learning algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning.
  • 2+ years of experience successfully leading technical teams.
  • Experience building customer platforms and exhibiting platform and data governance.
  • Understanding of causality principles and modeling of incrementality.
  • Familiarity with customer lifetime value, retention, and churn models.
  • Experience managing and influencing stakeholders and product owners.

Nice-to-haves

  • Experience with project management and demonstrated success in managing multiple tasks and projects.
  • Strong interpersonal skills and a highly collaborative work style.
  • Ability to train, mentor, and evaluate the technical capabilities of others.

Benefits

  • Medical, dental, and vision insurance coverage.
  • Health Savings Account and Flexible Spending Accounts.
  • Retirement savings plan with company and matching contributions.
  • Sickness and accident benefits.
  • Life insurance coverage.
  • Paid vacation and holidays, including parental leave.
  • Tuition assistance programs and student loan refinancing.
  • Employee assistance program and GM vehicle discounts.
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