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Vice President Machine Learning Jobs in Texas (NOW HIRING)

Meta

Vice President, Content Studio

Austin, TX

$451K/yr

Meta is seeking a Vice President of Content Studio to lead our in-house social within the ... Please note that Meta may leverage artificial intelligence and machine learning technologies in ...

Stout Risius Ross, LLC

Vice President

Dallas, TX

Seeking a Vice President/Sr. Vice President for our growing Accounting & Reporting Advisory ... To foster employee development we offer ongoing training and learning opportunities, employee ...

Stout Risius Ross, LLC

Vice President

Houston, TX

Seeking a Vice President/Sr. Vice President for our growing Accounting & Reporting Advisory ... To foster employee development we offer ongoing training and learning opportunities, employee ...

Woodmac

Vice President - Research

Houston, TX

Curious - we turn knowledge into action Vice President, Head of Americas Oil Markets Role ... and machine-learning-enhanced offerings across crude, oil products, and NGLs, bringing subject ...

Wood Mackenzie

Vice President - Research

Houston, TX · On-site

Curious - we turn knowledge into action Vice President, Head of Americas Oil Markets Role ... and machine-learning-enhanced offerings across crude, oil products, and NGLs, bringing subject ...

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All JobsVice President Machine Learning JobsVice President Machine Learning Jobs in Texas

Vice President Machine Learning information

See Texas salary details

$33.1K

$106.9K

$169.1K

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

As of Jul 25, 2026, the average yearly pay for vice president machine learning in Texas is $106,887.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $133,200.00 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, and why are they important?

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.

What are the most commonly searched types of Machine Learning jobs in Texas? The most popular types of Machine Learning jobs in Texas are:
What are popular job titles related to Vice President Machine Learning jobs in Texas? For Vice President Machine Learning jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Vice President Machine Learning jobs in Texas look for? The top searched job categories for Vice President Machine Learning jobs in Texas are:
What cities in Texas are hiring for Vice President Machine Learning jobs? Cities in Texas with the most Vice President Machine Learning job openings:
Vice President Machine Learning jobs near you

VP, AI Strategy & Solutions

Security Service FCU

San Antonio, TX

Full-time

Posted 16 days ago

Job description

VP of AI Strategy & Solutions serves as the chief architect of our data-driven vision, demonstrating a deep understanding of strategic planning, our current AI models, and the multiple products of artificial intelligence that are most impactful to financial institutions. Reporting directly to the SVP, Enterprise Technology Solutions, you will be entrusted with developing, scaling, and continuously refining our AI strategy, ensuring it leverages our existing tools and technologies while aligning with organizational priorities and values. This role will be instrumental in transitioning our $14 billion institution toward a proactive, AI-integrated enterprise focused on high member engagement and operational excellence. The role strategically defines, establishes, and leads an AI-focused operating unit, providing strategic guidance on the AI roadmap, AI compliance, enterprise priorities, solution deployments, technical architectures, and the maturation of our data ecosystem. Leverages existing AI products, models and technologies-including but not limited to Generative AI, CoPilot Agent solutions, Robotic Process Automation, Machine Learning, predictive lending models, and intelligent fraud prevention systems-to drive measurable value for the credit union and its members. Creates and implements enterprise wide policies for ethical and secure AI use, ensuring all initiatives are contained, controlled, and in harmony with our brand reputation and risk tolerance. The VP maintains the ability to reassess and retract AI initiatives if they prove overly aggressive or misaligned with SSFCU's values, consistently safeguarding the integrity and trust of our institution.

AI Roadmap & Governance: Champions, designs and executes a multi-year AI strategy that prioritizes high-impact use cases (e.g., hyper-personalized member marketing, real-time fraud detection, and automated credit decisioning), Collaborates with internal departments and works within the credit union overarching AI Risk and Governance program. Establishes and enforces organization-wide policies for ethical and secure AI adoption, making sure all initiatives are controlled, well-contained, and reflect the credit union's risk tolerance.

Data Ecosystem Leadership: Oversees the modernization of data repository architectures, ensuring our data is secure, clean, accessible, and robust to fuel selected AI capabilities and solutions.

Operational Innovation: Partners with business unit leaders (e.g., Lending, Retail, Risk Management) to identify friction points that can be solved through automation and AI, driving a lower Efficiency Ratio across the organization.

Vendor & FinTech Integration: Evaluates and manages relationships with AI service providers and FinTech partners to accelerate our speed-to-market for valuable new intelligent solutions, functions and features.

Financial Services Expertise: 7+ years of leadership in Data Science, AI, or Digital Transformation within a regulated financial environment. Proven Track Record: Experience taking AI/ML models from a "proof of concept" to full-scale production in a multi-channel environment. Educational Foundation: MBA with a technical focus or an advanced degree in Data Science, Computer Science, Mathematics or a related field is preferred.

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