Senior Technical Program Manager - ML/AI

Own and drive complex, cross-team ML/AI programs end-to-end — from scoping and planning through execution and launch — across model infrastructure, inference pipelines, AI functions, Cortex AI services, and AI-powered application features

Partner with ML Engineers, Research Scientists, Product Managers, and Engineering Leaders to define program roadmaps, surface dependencies, and build execution plans that account for the unique uncertainty and iteration cycles inherent to ML/AI development

Coordinate cross-org launches for AI features that span ML infrastructure, application surfaces (Streamlit, Notebooks, Cortex Code), and core platform — ensuring all teams ship cohesively and on time

Navigate the ambiguity of AI development — adapt program structures to handle model experimentation cycles, evaluation gates, accuracy/latency tradeoffs, and the non-linear nature of ML research-to-production timelines

Establish program governance and reporting cadences — track milestones, risks, decisions, and engineering health with clarity and rigor, and proactively escalate to leadership when programs need intervention

Drive cross-functional alignment between ML/AI engineering, product, design, infrastructure, security, and legal/compliance teams on AI feature launches, model deployment, and responsible AI practices

Identify and resolve systemic execution bottlenecks — design lightweight processes and tooling-backed workflows that improve engineering velocity without adding overhead

Own AI launch readiness — coordinate model evaluation sign-off, performance benchmarking, safety review, and documentation across engineering, product, and trust/safety teams

Represent ML/AI programs to senior leadership with crisp, data-backed status updates and strategic recommendations that connect program execution to business outcomes

Required:

5+ years of technical program management experience at a cloud or AI-native technology company, with a track record of owning cross-team programs end-to-end

Demonstrated experience with ML/AI programs — you understand the ML development lifecycle (training, evaluation, deployment, monitoring) and can manage programs around its unique iteration patterns and uncertainty

Strong technical depth — ability to engage meaningfully with ML engineers and research scientists on model architecture, inference infrastructure, evaluation metrics, and deployment tradeoffs

Proven ability to operate in ambiguity — ML/AI programs don't follow predictable timelines; you know how to structure execution around experimentation cycles and adapt plans as signals emerge

Experience managing programs spanning 4+ engineering teams with competing roadmaps and shared dependencies

Excellent communication skills — you synthesize complex technical and research concepts into clear, actionable narratives for leadership, product, and cross-functional audiences

Strong program management fundamentals: dependency management, risk frameworks, milestone governance, stakeholder alignment, and escalation discipline

Preferred:

Experience with LLM inference, fine-tuning, RAG architectures, or AI function platforms at production scale

Background in model serving infrastructure, GPU/accelerator resource management, or ML platform engineering

Familiarity with responsible AI practices — model evaluation, bias detection, safety review, and compliance workflows

Experience with Snowflake's architecture or data cloud ecosystem

Working knowledge of ML observability — monitoring model performance, drift detection, and production quality metrics

Background in launching customer-facing AI features where accuracy, latency, and cost are critical tradeoffs

Get It Done — You turn the inherent ambiguity of ML/AI into executable plans and deliver outcomes. You don't wait for perfect clarity — you create it.

Own It — You treat your programs as your own end-to-end. You anticipate risks before they surface and drive resolution without being asked.

Make Each Other the Best — You build bridges across ML research, engineering, and product. You create shared context and alignment that makes the whole organization move faster.

Think Big — You see beyond the current sprint. You think about what it takes for Snowflake's AI capabilities to operate at 10x scale and help build the frameworks to get there.

Snowflake is committed to pay equity and transparency. Actual compensation will be determined based on factors including relevant experience, skills, location, and internal equity.

Base Salary RangeTotal Target Compensation$166,000 – $249,000$190,900 – $286,350

In addition to base salary and bonus (15% target), this role is eligible for equity in the form of RSUs and a comprehensive benefits package including medical, dental, vision, 401(k), ESPP, generous PTO, and more.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.

How do you want to make your impact?

For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com