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Vice President Machine Learning Jobs in Michigan

Vice President, Engineering

Ann Arbor, MI ยท On-site

$176K - $227K/yr

As the VP of Engineering at S-Docs, you will be responsible for leading the execution, delivery ... Foster a culture of accountability, collaboration, and continuous learning across a distributed ...

Vice President, Engineering

Ann Arbor, MI ยท On-site

$176K - $227K/yr

As the VP of Engineering at S-Docs, you will be responsible for leading the execution, delivery ... Foster a culture of accountability, collaboration, and continuous learning across a distributed ...

Job Summary The Vice President, Construction Services provides strategic leadership, direction, and ... plenty of learning and growth. In exchange, we will reward you with great pay, advancement ...

Job Summary The Vice President, Construction Services provides strategic leadership, direction, and ... plenty of learning and growth. In exchange, we will reward you with great pay, advancement ...

VP Sales

Holland, MI ยท On-site

$150 - $230/hr

... and capping machinery for dairy, juice, water, food, chemical, coatings, and pharmaceutical ... The position reports to the Vice President & General Manager of FOGG FILLER. The position is a ...

Showing results 21-40

Vice President Machine Learning information

See Michigan salary details

$30.9K

$100K

$158.2K

How much do vice president machine learning jobs pay per year?

As of Sep 4, 2026, the average yearly pay for vice president machine learning in Michigan is $99,996.00, according to ZipRecruiter salary data. Most workers in this role earn between $82,800.00 and $124,600.00 per year, depending on experience, location, and employer.

What does a vice president of machine learning do?

A Vice President of Machine Learning leads and oversees the strategic direction of machine learning initiatives within an organization. They manage teams of data scientists, engineers, and researchers to develop and deploy AI-driven solutions that support business goals. This role involves collaborating with other executives, setting research agendas, ensuring best practices, and staying updated with the latest advancements in the field. The VP also plays a key role in resource allocation, talent acquisition, and scaling machine learning systems across the company.

What are the key skills and qualifications needed to thrive as a vice president of machine learning?

To thrive as a Vice President of Machine Learning, you need advanced expertise in machine learning, data science, and computer science, typically backed by a master's or PhD and extensive industry experience. Proficiency with platforms like TensorFlow, PyTorch, cloud computing services, and experience managing large-scale AI projects are crucial, along with a track record in leading technical teams. Exceptional leadership, strategic vision, and strong communication skills set outstanding candidates apart by enabling effective cross-functional collaboration and innovation. These skills are vital for driving organizational AI strategy, ensuring technical excellence, and delivering scalable business impact.

What are some common challenges faced by a vice president of machine learning when leading cross-functional teams?

A Vice President of Machine Learning often encounters challenges such as aligning diverse teams on technical priorities, managing expectations across product, engineering, and business units, and ensuring effective communication between stakeholders with varying levels of technical expertise. Balancing the need for innovation with practical business objectives and resource constraints is also a frequent challenge. Cultivating a collaborative culture and fostering ongoing professional development are key to overcoming these hurdles and driving successful outcomes.

What is the difference between Vice President Machine Learning vs Director of Machine Learning?

AspectVice President Machine LearningDirector of Machine Learning
Required CredentialsAdvanced degrees (Master's/PhD), extensive experience in MLSimilar educational background, less senior experience needed
Work EnvironmentStrategic leadership, cross-departmental collaborationProject management, team oversight
Employer & Industry UsageLarge tech firms, enterprises with AI focusTech companies, startups, research labs
Search & Comparison IntentHigh overlap in responsibilities and qualificationsRelated but more operational role

The Vice President Machine Learning typically holds a senior leadership role focused on strategic planning and cross-functional collaboration, while the Director of Machine Learning manages day-to-day projects and teams. Both roles require advanced degrees and experience in machine learning, but the VP is more involved in high-level decision-making and industry strategy.

What are the most commonly searched types of Machine Learning jobs in Michigan?

The most popular types of Machine Learning jobs in Michigan are:

What job categories do people searching Vice President Machine Learning jobs in Michigan look for?

The top searched job categories for Vice President Machine Learning jobs in Michigan are:

Infographic showing various Vice President Machine Learning job openings in Michigan as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $99,996 per year, or $48.1 per hour.

Vice President, Engineering

S-Docs Inc

Ann Arbor, MI โ€ข On-site

$176K - $227K/yr

Full-time

Re-posted 20 days ago


Job description


Role Description


Position Title: 

VP Engineering

Team:

Reports To:

Direct Reports:

Engineering

Chief Technology Officer

Yes


Role Purpose: 

As the VP of Engineering at S-Docs, you will be responsible for leading the execution, delivery, and people management of our Engineering organization, ensuring the reliable, scalable development of our document generation and e-signature platform. This role serves as a senior leader and key partner to the CTO, translating technical strategy into disciplined execution, delivery excellence, and team effectiveness.

You will own the day-to-day leadership of Engineering, including development velocity, quality, and team performance, while building strong operating rhythms, scalable processes, and a high-performing engineering culture. This role is global in nature, with responsibility for managing a distributed engineering organization that includes an offshore development team in India.

Working closely with Product, Customer Solutions, Customer Success, Support, and the broader Executive Leadership Team, you will ensure Engineering is aligned to business priorities, customer needs, and long-term platform scalability. This role is critical to enabling S-Docs’ continued growth while maintaining technical and operational excellence.

Key Job responsibilities:


  • Lead and manage the Engineering organization, ensuring consistent execution, delivery predictability, and high-quality outcomes across all engineering initiatives.

  • Will be hands on to driving architecture, design and development for product features and initiatives.

  • Drive quality control of the product delivered through automation and strong quality engineering processes.

  • Serve as the primary people leader for Engineering, building, mentoring, and retaining high-performing engineering leaders and teams.

  • Oversee and optimize global engineering operations, including direct leadership and partnership management of the offshore engineering team in India.

  • Establish and maintain strong operating cadences, development processes, and performance metrics to support scalable and reliable software delivery.

  • Partner closely with the CTO to translate architecture, product vision and technical strategy into actionable plans, roadmaps, and execution.

  • Collaborate cross-functionally with Product, Customer Solutions, Customer Success, and Support to ensure engineering efforts are aligned with customer needs and business priorities.

  • Drive continuous improvement in engineering practices, including code quality, testing, security, documentation, and deployment processes.

  • Support capacity planning, resourcing decisions, and prioritization to balance innovation, technical debt, and operational stability.

  • Foster a culture of accountability, collaboration, and continuous learning across a distributed, global engineering team.

  • Contribute to executive-level planning and decision-making. 


An ideal candidate for this position would have the following skills:


  • Deep working knowledge of the Salesforce platform that includes both declarative and programmatic capabilities.. 

  • Strong engineering leadership capability with the ability to balance strategic thinking and hands-on operational execution.

  • Deep understanding of modern SaaS architectures, cloud-based platforms, observability and enterprise-grade software development practices.

  • Deep understanding of enterprise architecture patterns and best practices with specific knowledge on Java, Postgres RDBMS, asynchronous processing via messaging platforms.

  • Strong working knowledge of i-PaaS integration platforms (e.g. Mulesoft, Workato etc.)

  • Deep understanding of  REST API architecture and design with special focus on security, authentication and authorization.

  • Deep understanding of security, cyber security best practices for cloud based applications

  • Strong knowledge of Large Language Models (LLM) and AI based technologies using frontier LLM models.

  • Proven ability to lead and scale distributed and global engineering teams across multiple time zones.

  • Exceptional people leadership skills, including coaching, performance management, and talent development.

  • Strong business acumen with the ability to align engineering outcomes to company goals and customer value.

  • Clear, confident communication skills with the ability to engage effectively with technical and non-technical stakeholders.

  • Self driven combined with curiosity , ability to explore and learn new technologies and paradigms.

  • A pragmatic, execution-oriented mindset with a focus on outcomes, reliability, and continuous improvement.


Experience:


  • 15+ years of professional experience in software engineering, with significant time spent in engineering leadership roles.

  • 10+ years of designing, and hands on development on the Salesforce platform

  • 8-10 years of designing and developing with Java, relational databases, REST APIs, enterprise architecture

  • Demonstrated success leading engineering teams within a SaaS or enterprise software environment.

  • Experience managing global engineering organizations, including offshore or outsourced development partners.