YOUR SKILLS & ABILITIES (REQUIRED QUALIFICATIONS)

• Bachelor’s degree (or equivalent work experience) in Computer Science, Data Science, or a related field.
• Minimum of 5 years of hands-on experience delivering enterprise-scale software products, with an emphasis on integrating machine learning models and Databricks workflows.
• Proven ability to lead engineering projects, mentor early-career developers, and collaborate effectively with data scientists, product managers, and non-technical stakeholders.
• Advanced proficiency in both front-end development (React, Angular, TypeScript, HTML/CSS) and back-end development (Node.js, Python, or Java).
• Deep understanding of hybrid-cloud and cloud-native software architecture, system design, and security, including microservices and containerization using Azure, Azure Key Vault, App Services, and Azure Kubernetes Services (or similar cloud platforms).
• Experience with CI/CD processes, including automated builds, deployments, and pipeline development.
• Demonstrated ability to collect, quantify, and communicate engineering quality and efficiency metrics.
• Experience working with Agile methodologies, including backlog grooming, sprint planning, and delivering solutions iteratively.
  

YOUR SKILLS & ABILITIES (REQUIRED QUALIFICATIONS)

• Familiarity with data science use cases and machine learning development lifecycle.
• Experience with Databricks Delta Lake, Ml f low, Unity Catalog .
• Experience with visualization tools and libraries including Power BI, D3.js, Plotly , or similar.
  This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate.

Compensation:

• The expected base compensation for this role is: $130,800 - $211,200. Actual base compensation within the identified 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 : 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.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE. THIS INCLUDES DIRECT COMPANY SPONSORSHIP, ENTRY OF GM AS THE IMMIGRATION EMPLOYER OF RECORD ON A GOVERNMENT FORM, AND ANY WORK AUTHORIZATION REQUIRING A WRITTEN SUBMISSION OR OTHER IMMIGRATION SUPPORT FROM THE COMPANY (e.g., H-1B, OPT, STEM OPT, CPT, TN, J-1, etc.)

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THE ROLE

We are looking for a full stack Senior Software Engineer to join the Applied Analytics & Insights - Digital, Customer & Portfolio organization, which focuses on leveraging data-driven solutions to optimize digital customer experiences and support strategic portfolio planning at GM. In this position, you will collaborate with product owners, data scientists, and partner teams to design , develop, and implement analytics applications that improve customer experience and bu siness outcom es , with an initial focus on vehicle portfolio planning use cases.

What You ’ll Do

• Collaborate with analytics delivery , data science , and stakeholder teams within a matrixed reporting structure to deliver applications that train and serve machine learning models .
• L ead front-end and back-end software architecture , design , and development ensur ing alignment with GM technology and security standards.
• Implement software validation , testing , code review, documentation, and production monitoring processes to ensure user satisfaction, quality , and supportability.
• Work with partner teams such as infrastructure, architecture, and operations on platform managemen t and technology migrations as required .
• Provide on-call support as required .

• Keep up with new trends and technologies and actively seek ways to increase productivity , including using GenAI where appropriate .Encourage continuous learning, knowledge sharing, and development within the team and the broader software engineering community.