---
title: 'Senior Technical Program Manager - ML/AI at Snowflake'
canonical: 'https://feeny.ai/job/senior-technical-program-manager-ml-ai-snowflake-menlo-park-z37j2qgt7hjt'
type: 'job'
last_seen: '2026-10-16'
---

# Senior Technical Program Manager - ML/AI at Snowflake

- **Company:** [Snowflake](https://feeny.ai/companies/snowflake)
- **Location:** Menlo Park, CA
- **Compensation:** $166k–$238k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-10-10
- **Last confirmed live:** 2026-10-16
- **Apply:** https://jobs.ashbyhq.com/snowflake/2d66e411-c782-43d5-9ad5-389c4407f9c6

## Job description

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. AS A SENIOR TECHNICAL PROGRAM MANAGER — ML/AI, YOU WILL:

- 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

OUR IDEAL SENIOR TPM — ML/AI WILL HAVE: 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

## SNOWFLAKE VALUES WE'RE LOOKING FOR:

- 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.

## COMPENSATION

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](http://careers.snowflake.com)

## About Snowflake

## Company Overview
- **One-liner**: Snowflake provides an AI Data Cloud platform that enables enterprises to store, analyze, and securely share their data across multiple clouds and geographies.
- **Entity Type**: Public (NYSE: SNOW)
- **Headquarters**: Bozeman, Montana, United States
- **Founded**: 2012
- **Founders**: Not explicitly listed in the provided search results (widely known co-founders include Benoit Dageville, Thierry Cruanes, Marcin Zukowski – not verified in these search results)

## Core Business
- **Primary Industry**: Enterprise software, cloud data platform
- **Target Customers**: B2B, including large enterprises (e.g., hundreds of the world’s largest companies), mid-market, and SMBs
- **Mission**: “To Mobilize the World’s Data” (Glassdoor) and “empower every enterprise to achieve its full potential through data and AI” (Snowflake Careers page)

## Products & Services
- **Snowflake AI Data Cloud**: A unified, multi-cloud platform that combines data warehousing, data lakes, data sharing, and AI/ML capabilities. Customers can discover, share, and analyze data while running analytic workloads across public clouds (AWS, Azure, GCP).
- **Snowflake Marketplace**: A marketplace for discovering and accessing third‑party data sets and applications.
- **Snowflake‑Powered Applications**: Platform for building and deploying data‑intensive applications.

## Market Standing
- **Valuation/Market Cap**: Not directly provided in search results (as a public company, market cap fluctuates and is available on financial websites).
- **Key Metric**: Annual Revenue – $1 to $5 billion (USD) per Glassdoor.
- **Notable Investors/Partners**: Not explicitly mentioned in the search results (historically backed by Sequoia Capital, Dragoneer, etc. – not verified here).
- **Growth Signals**:
  - Named #1 on the 2023 Fortune Future 50 List ([Fortune.com](https://fortune.com))
  - Listed as a U.S. Best Large Place to Work by BuiltIn in 2024
  - Recognized as one of the “20 Coolest Cloud Software Companies” by CRN in 2022 and 2024
  - Headcount of 5,001–10,000 employees with 30 global locations; actively hiring
  - Revenue range $1B–$5B indicates strong scale

## Competitive Advantages
- **Multi‑Cloud Flexibility**: Operates across AWS, Azure, and GCP, avoiding vendor lock‑in.
- **Unified Data Experience**: One platform for data sharing, analytics, and AI, reducing silos.
- **Separation of Compute and Storage**: Allows independent scaling and cost efficiency (not detailed in provided sources, but a known differentiator).
- **Strong Ecosystem**: Data marketplace and extensive partner network.

## Strategic Focus
- **AI & Data Innovation**: The company’s current emphasis is on making “enterprise AI easy, efficient, and trusted” and integrating AI capabilities into the Data Cloud.
- **Global Expansion**: Active hiring across 30 locations indicates continued geographic growth.
- **Customer‑Centric Development**: Focus on empowering enterprises to achieve “full potential through data and AI.”

## Why Work Here
- **Culture**: Described as “driven by innovation, low egos, high bars, and collaboration” (Snowflake Careers page). Glassdoor rating of 3.9/5 overall (78% approve CEO).
- **Work‑Life Balance**: Glassdoor rates Work/Life Balance at 3.7/5; many remote and hybrid roles available (see Indeed listings).
- **Benefits**: “Benefits & Beyond” program includes competitive compensation, equity, career advancement programs, and commitment to pay equality and veteran hiring.
- **Engineering Focus**: Hiring process includes 2–4 week timeline with technical interviews; the company values impactful, project‑based work for all roles, including interns.
- **Recognition**: Named a Best Large Place to Work (BuiltIn 2024) and future‑focused by Fortune, signaling strong employer brand.

## Sources
1. [Snowflake Careers Overview](https://careers.snowflake.com/us/en)
2. [Life at Snowflake](https://careers.snowflake.com/us/en/snowflake-life)
3. [Snowflake on Glassdoor](https://www.glassdoor.com/Overview/Working-at-Snowflake-EI_IE928471.11,20.htm)
4. [Snowflake Hiring Process](https://careers.snowflake.com/us/en/gethired)
5. [Snowflake on Indeed](https://www.indeed.com/cmp/Snowflake-7f4a7fba)
6. [Snowflake Careers Portal (Ashby)](https://jobs.ashbyhq.com/snowflake) – provided by user

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