Associate Director, Machine Learning & AI Engineering

Company description

Spark Foundry is a global media agency that exists to bring HEAT – Higher Engagement, Affinity, and Transactions – to brands. By combining flawless media fundamentals with aggressive innovation, Spark inspires consumers to pay more attention, to care more about our clients’ brands, and to buy more products and services from them.

Balancing the nimble spirit of a startup with the powerhouse soul of Publicis Media, Spark Foundry delivers the Զbest of both worlds to a client roster that spans some of the world’s best and most beloved brands and companies. We combine heuristic‑caliber insights and service with the buying clout and first‑look access of a global leader, bringing the heat to challenger brands that want to act like giants, and to giant brands that want to act like challengers.

With a bottom‑up culture that celebrates diversity and aims for all voices to be heard, Spark has become a magnet for the industry’s best talent, with one of the best retention rates in the industry. And by applying a whole‑person approach to professional computing personal development, Spark develops a workforce that is well prepared for today’s challenges, contrast touyên poised to create meaningful careers in the years to come.

Because we know that heat arises the intersection of complementary forces, our professionals come from myriad disciplines and backgrounds: data, analytics, and insights, content and creative production, communications and strategy, finance and marketing, and sociology, psychology, and other liberal arts disciplines.

Associate Director, ML & AI is a senior, hands‑on engineering績 leader responsible for driving the design, development, and delivery of scalable ML & AI solutions. This role will own the technical direction of priority initiatives, establish engineering standards, and ensure high‑quality execution across data engineering and AI/ML use cases. You’ll build GenAI‑first solutions (LLM‑powered assistants, insight synthesis, workflow automation) alongside traditional ML systems (forecasting, optimization, recommendations).

This is a hands‑on, product‑ুহolated role for someone who ships production systems, not research prototypes.

The Associate Director will work closely with analytics and media teams to translate business requirements into robust technical solutions. This role is ideal for someone who enjoys building from scratch, setting direction, and unblocking teams
, while remaining deeply involved in hands‑on development.

• Own the technical design and architecture for GenAI and dernière ML solutions end to end
orks
• Define standards for LLM usage, RAG patterns, evaluation, and production readiness
• Make architectural tradeoffs across scalability, cost, latency, and model quality
• Ensure GenAI solutions are secure, observable, and built for real‑world use
• Lead development of GenAI applications, including LLM workflows, RAG pipelines, and inference services
• Build datastore and feature workflows to support GenAI and traditional ML use cases
• Develop production‑grade APIs and backend services using cloud‑native and distributed systems
• Troubleshoot complex issues across data quality, retrieval accuracy, model behaviour, and system performance
• Drive priority AI initiatives from concept through production deployment
• Break down ambiguous problems into clear technical tasks, milestones, and MVPs
• Own delivery timelines, dependencies, and technical risk management
• Partner with stakeholders to balance speed, scope, and long‑term maintainability
• Serve as primary technical point of contact for GenAI and ML initiatives
• Translate business workflows into scalable technical designs
• Support stakeholder and client  requiring deep technical context
• Ensure alignment between upstream data sources and downstream AI consumption
• Leverage and extend existing AWS and Databricks infrastructure for GenAI workloads
• Integrate vector databases anna orchestration frameworks, and ML platforms into a cohesive stack
• Establish monitoring, logging, and alerting for AI pipelines, cost, latency, and quality
• Promote secure, compliant, and cost‑aware engineering practices
• Mentor engineers and analysts…