Azure Transformation Operations Manager

Are you rigid with your data structures but open with your strategy? Are you excited about GM's Zero Future vision? The Data Governance Team is looking for someone to own the design and implementation of governance processes to support strategic objectives. Someone who will architect and ensure compliance with the governance practices and standards of metadata, data quality, reference data, etc.

The Azure Transformation Operations Manager is responsible for all aspects of the uptime and security of GM Enterprise Data Analytics and Insights AI/ML and BI data products and applications in production.

This is a technical role related to the instrumentation and quality checks required to “command” every step (with no step missed) – over an end-to-end solution. This role requires deep familiarity with PRODUCTION management of Azure and Databricks solutions that reach customers and stakeholders. While certain solutions will be batch and only require pipeline level ops – a key skill is the management of solutions that have real time requirements that will demand sub 200MS response times and 99.9n uptime. Candidates will be expected to have successfully run operations for real time applications for a period of time.

Candidate should have the ability to generate the right tests and processes as we build new cross functional capabilities . The best candidates will have a strong vision around operations – and the ability to “bring others along” and align on (1) data contracts, (2) creation of cross functional RACI expectations, (3) creation of shared single sources of truth for Operations, (4) Runbooks, (5) Overall documentation and (6) transition of successful products and applications – to a “Managed Service” team that will – over time

This candidate should “take ownership” of solutions and be focused on the delivery of value to the intended audience.

Note that this role is NOT – long term support of “Keep the Lights On” projects. This role requires this team to “ understand, instrument, launch, stabilize and transition” production applications to lower cost teams. This requires the ability to set standards, design and automate tests that ensure compliance with the defined standards.

We are creating new capabilities here at GM – and we are looking for a strong DevSecOps presence on our team to help us set the right precedent .

Skills & Qualifications:

• Deeply Technical regarding the intersection of code and infrastructure
• This role is NOT code to design ML solutions from scratch.
• Is responsible for the end -to- end data flow, the end- to -end timing charts, all latency implications, the overall MLC - including but not limited to distributed computing, data flows, connection management, caching strategies, pipeline quality, security compliance, dependencies.
• Is responsible for working with relevant Product Manager(s), Security, Data Scientists, ML Ops teams, Infrastructure teams, business partners, and measurement teams to ensure a shared vision. Able to take models - no matter the state of maturity - and help navigate all these groups to create consensus.
• Focused on the creation of value via AI/ML.
• This role is about creating highly dependable, cost effective, and "fully empowered" ML solutions. Our success criteria are measured in terms of the L3 incident count over time, the ongoing personnel costs and the cloud costs associated with the ML solution. The idea lead - "saves the company time, money, headaches, and allows for accelerated innovation" by freeing up these resources.
• Must have a decisive mindset, a growth mindset - and be focused on- "realizing" models in production. Must have a track record of working in Production.
• Focused on TCO and maintainability of models - for turn over to Managed Services (or third parties)
• Cross Functional Leader
• This role works with Data Scientists or third parties who are responsible for creating ML models (or PoCs of ML models). Evaluation, GAP analysis, code reviews and refactor support - is the key to this role. In certain cases - the ML Engineer will lean in on certain areas of focus to enable the overall team.

Requirements:

• Bachelor's, Master’s Degree or Ph.D. in Data Science, Analytics, Operations Research, Engineering, Statistics, Economics, Computer Science, Applied Mathematics, or another related field.
• 3 years of hands' on experience running a product AI or ML experience.

Remote: The position can be performed remotely from the US most of the time, but the employee may be asked to come on-site approximately four times per year

Compensation: The expected base compensation for this role is : $166,131 - $200,018 . 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.

#Remote

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.

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