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Product Manager - Deployment

Thinking MachinesSan FranciscoProduct Management
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Salary
$350K - $400K USD
Job type
Full-time
Work mode
Remote
Posted
4 Aug 2026
Status
Open · checked 7d ago

About this role

Thinking Machines is seeking a Product Manager for Deployment to lead how advanced AI models and fine-tuned checkpoints move into dependable production environments in San Francisco or remotely. This full-time position suits an experienced product leader with a strong technical background who wants to shape the future of machine learning infrastructure and deployment workflows.

Role Overview

In this position, the product manager takes charge of the entire journey from a trained model to a reliable, cost-efficient endpoint. The scope includes inference infrastructure, serving APIs, latency and throughput balancing, scaling behavior, observability, and user workflows. Because deployment practices at Thinking Machines are actively evolving, the professional in this role will define what production readiness means for fine-tuned models, establish supported serving paths, and scale systems reliably as usage grows. This opportunity involves working closely with infrastructure, research, engineering, and go-to-market teams.

Key Responsibilities

Own the deployment strategy, product roadmap, and success metrics for transitioning models and Tinker-trained checkpoints into production.
Define priority deployment paths across model serving, autoscaling, versioning, rollback, monitoring, and incident response.
Engage at engineering depth regarding serving architecture, latency and cost tradeoffs, reliability targets, capacity planning, and API or SDK deployment surfaces.
Create direct feedback loops with users deploying models in production to identify pain points and prioritize product enhancements.
Drive ambiguous technical workstreams end to end, handling technical scoping, dependency resolution, launch readiness, escalation design, and post-incident learning.
Connect deployment decisions to the wider model and infrastructure roadmap while managing tradeoffs between flexibility, reliability, and operational cost.
Shape service level agreements, pricing and packaging inputs for hosted inference, and the operating model for a rapidly scaling deployment platform.
Execute hands-on tasks to ensure deployment success, such as reviewing serving configurations, participating in incident retrospectives, inspecting latency data, or drafting rollout plans.

Requirements

Experience owning a production machine learning serving, infrastructure, or deployment product, including direct involvement in reliability, scaling, or performance decisions.
Proven track record working at engineering depth with production systems, with comfort discussing latency, throughput, autoscaling, rollback, and incident response in detail.
Experience guiding a technical product from early usage stages through to reliable, scaled production deployment.

Nice to Have

Background working as an engineer or technical founder prior to transitioning into product leadership.
Familiarity with machine learning inference infrastructure specifically, such as model serving frameworks, GPU scheduling, batching, and quantization tradeoffs.
Experience operating within a startup, lab, or new product area where the deployment model and roadmap required definition from scratch.
Ability to transition seamlessly between high-level strategic narratives and granular technical details like autoscaling policies or service level agreements.
Experience building trust with technical users through evidence, responsiveness, and follow-through.

Skills and Tools

MLOps
Model serving frameworks and GPU scheduling
Inference infrastructure and API/SDK surfaces
Autoscaling, latency, and throughput optimization
Reliability, monitoring, and incident response systems

Salary and Benefits

Expected annual salary range of $350,000 to $400,000 USD, depending on background, skills, and experience.
Visa sponsorship available for qualified candidates.
Generous health, dental, and vision benefits.
Unlimited paid time off (PTO).
Paid parental leave.
Relocation support as needed.

About the Company

Thinking Machines builds artificial intelligence designed to extend human will and judgment. The organization is currently training frontier models using Inkling, developing Tinker to allow customized model creation, and crafting interfaces that improve human-AI communication.

How to Apply

Interested candidates should visit the official Thinking Machines careers page to submit an application for this position.

Skills and tech stack

MLOps

Questions candidates ask

What is the salary range for the Product Manager - Deployment role?

The expected annual salary range is $350,000 to $400,000 USD, depending on background, skills, and experience.

Where is this job located?

This role is based in San Francisco, California, with remote flexibility.

Does Thinking Machines offer visa sponsorship?

Yes, Thinking Machines provides visa sponsorship for eligible candidates selected for the role.

What benefits are included with employment?

Benefits include health, dental, and vision coverage, unlimited paid time off, paid parental leave, and relocation support if required.

What are the core technical focuses of this position?

The role focuses on ML inference infrastructure, model serving architecture, latency and cost tradeoffs, autoscaling behavior, and production reliability.

Ready to apply?

The application is on the official Thinking Machines careers page.

Apply on company site