Machine Learning / AI Contractor

Position Summary

Work you'll do

We are seeking a hands-on Machine Learning / AI Contractor to support the development and adoption of applied generative AI solutions across WPC Analytics. This role is focused on building practical AI tools, enablement assets, and workflows that help Data Scientists and partner teams use modern AI capabilities effectively in a production environment. The contractor will help evaluate, pilot, and scale AI use cases, with an emphasis on technical soundness, responsible use, and real-world business value.

Responsibilities

• Support the development and adoption of generative AI through collaboration, clear communication, and strong technical foundations.
• Partner with data science, software engineering, product, and other cross-functional teams to identify and deliver practical AI use cases.
• Serve as a technical advisor to software engineering teams, including work related to an organization-wide retrieval-augmented generation engine.
• Design, build, and pilot AI-enabled applications, tools, and workflows.
• Evaluate emerging AI technologies and validate their real-world utility before broader adoption.
• Develop training materials, best practices, implementation guidance, and playbooks for Data Scientists and partner teams.
• Help teams use modern AI tools effectively, responsibly, and consistently.
• Build observability and reporting capabilities for GitHub to improve visibility into AI usage, adoption, and impact.
• Translate complex AI concepts into clear recommendations for both technical and nontechnical stakeholders.
• Identify technical, operational, or business situations where generative AI may not be the appropriate solution.
• Promote practical approaches to AI quality, evaluation, monitoring, responsible use, and continuous improvement.

Required Qualifications

• 6–9 years of professional experience in machine learning, artificial intelligence, applied data science, software engineering, or a related field.
• Hands-on experience with generative AI engineering and the development of AI-enabled applications.
• Experience translating business or data science needs into practical technical solutions.
• Strong understanding of modern large language model capabilities, limitations, and application patterns.
• Experience working with cross-functional teams and influencing adoption through collaboration.
• Ability to communicate complex technical concepts clearly to technical and nontechnical audiences.
• Demonstrated ability to build prototypes, test solutions, evaluate results, and iterate based on real-world feedback.
• Strong software development fundamentals, including version control and collaborative development practices.
• Pragmatic approach to technology selection, with sound judgment regarding feasibility, value, risk, and maintainability.

Preferred Qualifications

• Experience designing or supporting retrieval-augmented generation solutions.
• Experience developing AI enablement programs, technical training, playbooks, or communities of practice.
• Experience with AI observability, usage analytics, evaluation frameworks, or developer productivity measurement.
• Experience partnering with software engineering and data science organizations.
• Familiarity with responsible AI principles, model evaluation, security considerations, and adoption governance.
• Experience piloting emerging AI tools in business or enterprise environments.
• Ability to operate effectively in ambiguous, fast-moving environments.

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