Hearst Technology Services is looking to develop and deliver AI "as-a-service" capabilities to empower its 360+ business brands, driving productivity, efficiencies, and revenue growth through AI solutions.
Requirements
- Proven track record of delivering AI/ML solutions in production (experience with Generative AI projects highly desired).
- Deep knowledge of AI/ML techniques, including natural language processing, machine learning frameworks, and cloud-based AI services.
- Hands-on experience with GPT or other large language models, and familiarity with RPA and other automation technologies.
- Strong understanding of MLOps, data pipelines, and deploying models at scale.
- Experience with Generative AI projects highly desired.
- Experience with GPT or other large language models.
Responsibilities
- Build and manage a portfolio of AI services and platforms (e.g. generative AI models, automation tools) that business units can opt into.
- Lead agile teams (pods/squads of data scientists, engineers, and business analysts) to design, develop, and deploy AI solutions from concept to production.
- Provide technical direction in cutting-edge AI areas, including large language models (GPT), retrieval-augmented generation (RAG), and autonomous AI “agents.”
- Guide the team in selecting the right approaches and tools for each project, and contribute hands-on to model development, validation, and integration when needed.
- Collaborate with external service providers and vendors to augment our capabilities.
- Implement AI governance and best practices across projects.
- Define clear engagement processes for business units to access AI services.
Other
- 10+ years of experience in technology roles with at least 5 years in AI/ML or data science leadership.
- 5+ years of managing teams or projects in a complex, cross-functional environment.
- Bachelor’s degree in Computer Science, Data Science, or related field; Master’s degree preferred.
- Strong leadership and team-building skills.
- Ability to manage and mentor a technical team, while also effectively communicating with non-technical stakeholders.
