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About This Role
Senior Product Manager — Spatial AI & 3D CAD Systems
Location: San Francisco, CA (100% On‑Site) Work Authorization: US Citizen or Green Card Holder Relocation: $5K–$10K available Industry: 3D CAD CAE PLM Manufacturing Aerospace & Defense
Company Overview (Confidential)
We are a cutting‑edge spatial intelligence AI startup building foundational models purpose‑built for physical engineering and manufacturing design. Backed by $27M in venture funding led by Khosla Ventures, our team includes alumni from Meta, Autodesk Research, Stanford, MIT, and CMU.
Our core technology centers on SGS‑2 spatial foundation models capable of understanding, designing, and reasoning about complex 3D mechanical systems. We integrate deeply with leading 3D CAD platforms and engineering software to unlock next‑generation automated design workflows.
Technical & Product Environment
- Spatial Foundation Models: SGS‑2 models optimized for 3D CAD design, automated engineering workflows, and physical system generation.
- Tech Stack: SolidWorks, Siemens NX, CATIA, Onshape, Autodesk Fusion 360; Python, C++; CAE simulation tools.
- Target Users: Aerospace, defense, advanced manufacturing, industrial software teams.
About the Role
As Senior Product Manager, you will sit at the intersection of spatial AI research, 3D CAD engineering workflows, and early GTM execution. You will transform raw model capabilities into compelling user‑facing products, partner with early design customers, and shape the roadmap for next‑generation engineering intelligence.
What You'll Do
- Build Interactive Demos & Prototypes: Create user‑facing demos, prototype workflows, and test datasets that translate spatial model outputs into practical engineering tools.
- Lead CAD/CAE Domain Evaluation: Apply deep mechanical design expertise to assess spatial model output quality against real‑world engineering standards.
- Drive GTM & Partner Engagement: Work directly with early manufacturing, aerospace, and defense partners to identify workflows, bottlenecks, and high‑value use cases.
- Shape Research & Product Roadmap: Convert customer requirements into technical priorities that guide the core AI engineering roadmap.
Who You Are/Requirements
- Experienced PM: 6–10 years of product management experience in industrial software (3D CAD, CAE, PLM), manufacturing tech, or aerospace/defense software.
- Technically Fluent: Hands‑on mastery of major 3D CAD systems (SolidWorks, NX, CATIA, Onshape) and ability to write Python/C++ for internal tooling.
- Customer‑Centric: Comfortable working directly with engineering teams and technical partners to refine workflows and validate product direction.
- On‑Site Operator: Able to work in‑person 5 days/week in San Francisco.
Pay: $200,000.00 - $300,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Employee assistance program
- Employee discount
- Flexible schedule
- Health savings account
- Life insurance
- Paid time off
- Parental leave
- Retirement plan
- Tuition reimbursement
Application Question(s):
- Have you ever worked for a start-up company? If so, what measurable impact did you have on the company?
Work Location: In person
Salary Context
This $200K-$300K range is above the 75th percentile for AI Product Manager roles in our dataset (median: $185K across 149 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 10,827 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At EZ Recruitment, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $220,350 based on 994 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($250K) sits 13% above the category median. Disclosed range: $200K to $300K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,300; VP: $236,450.
EZ Recruitment AI Hiring
EZ Recruitment has 1 open AI role right now. They're hiring across AI Product Manager. Based in San Francisco, CA, US. Compensation range: $300K - $300K.
Location Context
AI roles in San Francisco pay a median of $260,600 across 2,767 tracked positions. That's 22% above the national median.
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 10,827 open positions tracked in our dataset. By seniority: 122 entry-level, 5,256 mid-level, 3,922 senior, and 1,527 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (665 positions). The remaining 10,097 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,111. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 10,827 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,288), AI Software Engineer (548), AI Product Manager (471). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (122) are outnumbered by mid-level (5,256) and senior (3,922) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,527 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (665 positions), with 10,097 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,480. Top-quartile roles start at $264,111, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $266,050 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,093 postings), Aws (1,100 postings), Azure (910 postings), Rag (863 postings), Gcp (680 postings), Pytorch (549 postings), Claude (532 postings), Kubernetes (511 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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