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Vice President Machine Learning Jobs (NOW HIRING)

Steg.AI

VP of Engineering

Irvine, CA · On-site

$180 - $280/hr

AI is looking for a highly motivated Vice President of Engineering with a passion for leading teams to create groundbreaking machine learning products for watermarking, steganography, or media ...

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Vice President Machine Learning information

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$35.5K

$114.7K

$181.5K

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

As of Aug 14, 2026, the average yearly pay for vice president machine learning in the United States is $114,728.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,000.00 and $143,000.00 per year, depending on experience, location, and employer.

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 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 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.

Is vice president machine learning a high paying job?

The Vice President of Machine Learning is typically a high-level executive role with a competitive salary that reflects expertise in AI, data science, and leadership. Salaries often range from six to seven figures depending on the industry, company size, and location.

What cities are hiring for Vice President Machine Learning jobs?

Cities with the most Vice President Machine Learning job openings:

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

The most popular types of Machine Learning jobs are:

What states have the most Vice President Machine Learning jobs?

States with the most job openings for Vice President Machine Learning jobs include:

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

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

Vice President Machine Learning jobs near you
Infographic showing various Vice President Machine Learning job openings in the United States 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 $114,728 per year, or $55.2 per hour.

VP, Machine Learning Engineer, Enterprise AI, Innovation Group

UOB

Central, LA • On-site

$120 - $150/hr

Other

Posted 9 days ago

Job description

## VP, Machine Learning Engineer, Enterprise AI, Innovation GroupApplyremote type: Onsitelocations: Central Region (City Area)time type: Full timeposted on: Posted 7 Days Agojob requisition id: JR88245Company: 1011 United Overseas Bank Ltd **About UOB**United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices. Our history spans more than 80 years. Over this time, we have been guided by our values – Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.**Job Description****About the Department**Enterprise AI (EAI) focus on delivering AI and machine learning models developed in collaboration with business and support units, and driving the adoption of GenAI self-help across the Bank for value creation. EAI will spearhead the AIDA Center of Excellence, as well as own and manage the enterprise AI platforms.**Role Overview**UOB Enterprise AI is looking for an experienced and innovative AI Platform Specialist to join the dynamic team.You will be expected to play an integral role in shaping and executing our AI strategy and enterprise AI platform, leverage your expertise in ML algorithms, architectures, and best practices to design, develop, and deploy high-impact AI solutions that solve real-world banking challenges and create significant value for the enterprise.**Key Responsibilities:*** Partner with group technology to develop and enhance enterprise AI platform and operation to help drive AI industrialization within the bank.* Act as AI platform SME and work closely with data scientists, IT engineers and business stakeholders to understand the business needs, develop end-to-end ML solutions, and deploy into production environment.* Design and develop re-useable assets, libraries, frameworks, and ML tools to accelerate model development and platform management.* Collaborate with technology team to adopt best-in-class industry practices to streamline model deployment processes.* Build and optimize data and ML pipeline to ensure robust and high-quality data feed for both model training and operation.* Develop appropriate tools/apps/UIs to complete AI products for business stakeholders.* Stay ahead of industry trends, emerging technologies, and best practices to drive continuous improvement AI/ML process in UOB.**Key Requirement:*** Bachelor’s or advanced degree in computer science, data science, software engineering or related fields.* Minimum 8 years of experience as an ML Engineer or similar role, with proven track record of developing and deploying ML solutions into production environment.* In-depth knowledge of ML algorithms, development tools, model life cycle and deployment patterns.* Hands-on experience of data management technology, including Hadoop, Sparks, ETL, relational & non-relational databases.* Proficiency in programming languages such as Python, Java or Scala.* Experience in on-premises and cloud-based AI platforms and technologies; familiar with DevOps and CI/CD practices.* Strong communication skills and able to convey/articulate complex technical concepts to non-technical stakeholders.* Working experience in banking/financial sector is a plus.## **Additional Requirements**University-BachelorBe a Part of the UOB FamilyUOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application. #J-18808-Ljbffr

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