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Vice President Machine Learning Jobs in Springfield, MA

The SVP, Chief Technology Officer (CTO) is the executive responsible for defining and executing the ... Lead enterprise implementation of Generative AI, Machine Learning, Intelligent Automation, and ...

... of learning and excellence within the team. The Team Our Hybrid Cloud Infrastructure offering ... AI Datacenter & Infrastructure Associate VP Join our AI & Engineering team and help transform ...

Administrative Assistant

Holyoke, MA ยท On-site

$23.98 - $32.37/hr

Serves as Administrative Assistant to VP/Chief Nursing Officer and VP/Chief Financial Officer ... Runs mail through postage machine and maintains all supplies and maintenance request for postage ...

Serves as Administrative Assistant to VP/Chief Nursing Officer and VP/Chief Financial Officer ... Runs mail through postage machine and maintains all supplies and maintenance request for postage ...

Serves as Administrative Assistant to VP/Chief Nursing Officer and VP/Chief Financial Officer ... Runs mail through postage machine and maintains all supplies and maintenance request for postage ...

Administrative Assistant

Holyoke, MA ยท On-site

$23.98 - $32.37/hr

Serves as Administrative Assistant to VP/Chief Nursing Officer and VP/Chief Financial Officer ... Runs mail through postage machine and maintains all supplies and maintenance request for postage ...

AVP Applied AI

Hartford, CT ยท On-site +1

The Assistant Vice President (AVP), Applied AI leads data science, traditional machine learning, and agentic AI capabilities supporting The Hartford's Business Insurance. This role partners closely ...

... learning appropriate self-care techniques. * Supervises LPNs and HHAs. * Completes documentation ... VP Clinical.* * Current RN license, specific to the state(s) you are assigned to work. * Current ...

Facilities Operations Assistant

Hartford, CT ยท On-site

$37K - $46K/yr

Under the direction of the Vice President of Facilities, Real Estate & Infrastructure Planning ... learning disability or physical disability, veteran status, sexual orientation, genetic information ...

Showing results 21-40

Vice President Machine Learning information

See Springfield, MA salary details

$35.4K

$114.3K

$180.9K

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 Springfield, MA is $114,327.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,700.00 and $142,500.00 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 are the most commonly searched types of Machine Learning jobs in Springfield, MA?

The most popular types of Machine Learning jobs in Springfield, MA are:

What job categories do people searching Vice President Machine Learning jobs in Springfield, MA look for?

The top searched job categories for Vice President Machine Learning jobs in Springfield, MA are:

What cities near Springfield, MA are hiring for Vice President Machine Learning jobs?

Cities near Springfield, MA with the most Vice President Machine Learning job openings:

Infographic showing various Vice President Machine Learning job openings in Springfield, MA 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 $114,327 per year, or $55 per hour.

SVP, Chief Technology Officer (CTO)

Kemper

Hartford, CT โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 14 days ago


Job description

Location(s)

Alpharetta, Georgia, Annapolis, Maryland, Birmingham, Alabama, Boston, Massachusetts, Buffalo, New York, Chicago, Illinois, Dallas, Texas, Des Moines, Iowa, Dover, Delaware, Downers Grove, Illinois, Harrisburg, Pennsylvania, Hartford, Connecticut, Indianapolis, Indiana, Jacksonville, Florida, Las Vegas, Nevada, Little Rock, Arkansas, Oklahoma City, Oklahoma, Phoenix, Arizona, Raleigh, North Carolina, Remote-GA, Remote-IA, Remote-IL, Remote-MI, Remote-NJ, St. Louis, Missouri

Details

Kemper is one of the nation's leading specialized insurers. Our success is a direct reflection of the talented and diverse people who make a positive difference in the lives of our customers every day. We believe a high-performing culture, valuable opportunities for personal development and professional challenge, and a healthy work-life balance can be highly motivating and productive. Kemper's products and services are making a real difference to our customers, who have unique and evolving needs. By joining our team, you are helping to provide an experience to our stakeholders that delivers on our promises.

The SVP, Chief Technology Officer (CTO) is the executive responsible for defining and executing the enterprise technology strategy through four strategic pillars:

  • Cloud & Platform Engineering
  • Enterprise Data Engineering
  • Artificial Intelligence & Intelligent Automation
  • Enterprise Architecture & Technology Innovation

The CTO is accountable for building and operating the secure, scalable, cloud-native technology platforms that enable the business to innovate, modernize, and compete. This includes enterprise cloud infrastructure, developer platforms, data platforms, AI platforms, integration capabilities, and shared technology services that support all business functions.

A critical responsibility of this role is ensuring Artificial Intelligence delivers measurable business value. The CTO partners with executive leadership to identify opportunities where AI can fundamentally redesign business processes, improve customer and employee experiences, accelerate decision-making, and create competitive advantage. Success is measured not by AI experimentation, but by enterprise adoption, business transformation, and quantifiable business outcomes.

The CTO works in partnership with the CIO to shape the long-term technology vision while ensuring technology investments improve enterprise agility, resiliency, operational efficiency, and innovation.

Key ResponsibilitiesEnterprise Technology Strategy
  • Develop and execute the enterprise technology strategy aligned with business objectives and long-term growth.
  • Establish technology roadmaps that modernize enterprise capabilities through cloud-native platforms, automation, data, and AI.
  • Advise the organization on emerging technologies, technology investments, and innovation opportunities.
  • Drive enterprise technology standards, governance, architecture, and technology lifecycle management.
Cloud & Platform Engineering

Lead the strategy, engineering, and operation of enterprise technology platforms, including:

  • Public and hybrid cloud infrastructure
  • Platform Engineering
  • Kubernetes and container platforms
  • Infrastructure as Code (IaC)
  • DevSecOps and CI/CD platforms
  • Site Reliability Engineering (SRE)
  • Enterprise observability and monitoring
  • Identity and shared platform services
  • FinOps and cloud optimization

Build highly automated, resilient, secure, and scalable technology platforms that accelerate software delivery while improving operational excellence and reducing total cost of ownership.

Enterprise Data Engineering

Define and lead the enterprise Data Engineering strategy supporting analytics, operational reporting, AI, and digital products.

Responsibilities include:

  • Modern cloud-based data platforms
  • Enterprise data lakehouse architecture
  • Data governance and metadata management
  • Data quality and lineage
  • Master Data Management
  • Enterprise data security

Demonstrated expertise is required across multiple enterprise data integration patterns including:

  • Batch processing
  • API-based integration
  • Event-driven architectures
  • Real-time streaming platforms

Ensure enterprise data is trusted, governed, secure, reusable, and accessible to support business intelligence and AI initiatives.

Artificial Intelligence & Intelligent Automation

Develop and execute the enterprise AI strategy focused on measurable business value creation.

Responsibilities include:

  • Identify high-value AI opportunities in partnership with business leaders.
  • Consult with business executives to redesign business processes that leverage AI rather than simply automating existing human workflows.
  • Lead enterprise implementation of Generative AI, Machine Learning, Intelligent Automation, and Agentic AI capabilities.
  • Build and operate enterprise AI platforms supporting secure and scalable AI adoption.
  • Establish Responsible AI governance, model lifecycle management, and AI risk management.
  • Create repeatable frameworks for identifying, prioritizing, implementing, and scaling AI use cases across the enterprise.
  • Drive enterprise AI literacy through executive education, workforce training, change management, communications, and adoption programs.
  • Measure AI success through quantifiable business outcomes including productivity improvements, expense reduction, revenue growth, customer satisfaction, and operational efficiency.

Candidates must demonstrate a proven track record of leading enterprise AI implementations that progressed beyond pilot programs to production deployment with measurable business value.

Enterprise Architecture & Technology Innovation

Lead Enterprise Architecture to ensure technology investments create reusable enterprise capabilities rather than siloed solutions.

Drive innovation through:

  • Emerging technology evaluation
  • Technology incubation
  • Strategic partnerships
  • Cloud hyperscaler relationships
  • AI ecosystem partnerships
  • Technology standards and reference architectures

Guide enterprise modernization initiatives while ensuring technology investments remain aligned with business strategy.

Executive Leadership & Governance

Build and lead high-performing organizations across:

  • Cloud & Platform Engineering
  • Enterprise Data Engineering
  • Enterprise Architecture
  • AI & Intelligent Automation
  • Technology Innovation

Establish a culture of engineering excellence, innovation, accountability, continuous learning, and business partnership.

Oversee technology investment planning, vendor strategy, technology risk, operational resiliency, regulatory compliance, and executive performance reporting.

Qualifications
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related discipline; Master's degree, MBA, or advanced technical degree preferred.
  • 15+ years of progressive technology leadership with at least 5 years in executive leadership roles within large, regulated enterprises.
  • Deep expertise leading Cloud & Platform Engineering organizations supporting enterprise-scale digital capabilities.
  • Demonstrated success implementing cloud-native platforms utilizing Infrastructure as Code, Platform Engineering, DevSecOps, Kubernetes, observability, automation, and Site Reliability Engineering.
  • Extensive experience leading Enterprise Data Engineering organizations, including modern cloud data platforms and enterprise integration using batch, APIs, event-driven architectures, and streaming technologies.
  • Proven success delivering enterprise AI solutions that achieved measurable business outcomes through production implementation, organizational adoption, and business process transformation.
  • Demonstrated leadership in AI strategy, AI governance, responsible AI, enterprise AI platforms, AI literacy, organizational change management, and executive consulting.
  • Strong understanding of cloud security, enterprise architecture, technology governance, and regulatory environments within financial services or insurance.
  • Exceptional executive communication skills with the ability to influence Boards of Directors, executive leadership teams, regulators, and strategic technology partners.
  • Proven ability to attract, develop, and inspire world-class engineering and technology leaders while fostering a culture of innovation, accountability, and continuous improvement.
  • This role can work at a Kemper office or remotely from a US based home.

The range for this position is $250,000 to $350,000. Whendeterminingcandidate offers, we consider experience, skills, education, certifications, and geographic location among other factors. This job is eligible for an annual discretionary bonus, equity and Kemper benefits (Medical, Dental, Vision, PTO, 401k, etc.).

Kemper is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, disability status or any other status protected by the laws or regulations in the locations where we operate. We are committed to supporting diversity and equality across our organization and we work diligently to maintain a workplace free from discrimination. Kemper is focused on expanding our Diversity, Equity and Inclusion efforts to align with our vision, mission, and guiding principles.

Kemper does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Kemper and Kemper will not be obligated to pay a placement fee.

Kemper will never request personal information, such as your social security number or banking information, via text or email. Additionally, Kemper does not use external messaging applications like WireApp or Skype to communicate with candidates. If you receive such a message, delete it.

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