---
title: 'Senior / Staff Technical Program Manager, AI Research at Rhoda AI'
canonical: 'https://feeny.ai/job/senior-staff-technical-program-manager-ai-research-rhoda-ai-mountain-view-vwmnc9zskvbs'
type: 'job'
last_seen: '2026-10-28'
---

# Senior / Staff Technical Program Manager, AI Research at Rhoda AI

- **Company:** Rhoda AI
- **Location:** Mountain View, CA
- **Employment:** full-time
- **Posted:** 2026-10-23
- **Last confirmed live:** 2026-10-28
- **Apply:** https://jobs.ashbyhq.com/rhoda-ai/c051195c-8b91-4f62-b0ab-28109c0626cc

## Job description

At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.

## The role

We're looking for a Senior/Staff Technical Program Manager, AI Research to help scale how research programs come together at Rhoda. This is a deeply technical, cross-functional execution role at the intersection of pre-training, post-training, applied research, data, GPU infrastructure, robotic hardware, and customer-facing model delivery. You'll own the integrated execution plan across these efforts: connecting milestones, anticipating dependencies, driving blockers to resolution, and helping teams make timely resource and sequencing decisions. The objective is to give researchers and engineers more time to build, while making the path from research experiments to usable models more predictable. You'll work closely with Research leadership, technical leads, infrastructure, robotics, and hardware teams. You won't need to invent the scientific roadmap yourself—but you should be technical enough to understand it, challenge assumptions constructively, and turn ambiguity into practical options.

## What you'll do

- Build the integrated research roadmap. Translate individual project plans into a clear, continuously updated view of experiments, model and data readiness, system integrations, releases, dependencies, critical paths, and decision points.
- Connect model development to downstream use. Coordinate the transitions from pre-training checkpoints to post-training, applied model engineering, evaluation, and deployment; align on handoff criteria, owners, and readiness expectations.
- Synchronize data, compute, and hardware. Anticipate when training datasets, collection systems, robots, workcells, and GPU capacity need to be available; manage resource demand forecasts and routine scheduling trade-offs within agreed priorities.
- Drive blockers to resolution. Identify cross-team gaps before they become delays, bring the right owners together, maintain action plans and contingencies, and escalate consequential trade-offs with a concrete recommendation.
- Surface capacity and staffing risks early. Help research leaders understand where milestones need additional engineering capacity, specialized expertise, or reprioritization; support decisions without owning personnel management.
- Build lightweight execution rhythms. Run focused program reviews, maintain decision and dependency logs, and create concise, reliable updates for technical leadership without burying researchers in process.
- Manage uncertainty intelligently. Distinguish experiments, proof-of-concept demonstrations, engineering-readiness milestones, and customer-deployment commitments; track confidence and learning goals instead of forcing speculative research into false precision.
- Improve cross-functional execution. Partner with hardware and operations TPMs and program leads to clarify interfaces, ownership, acceptance criteria, and release expectations as Rhoda scales.

## What we're looking for

- Significant technical program management experience delivering complex, interdependent work across software, ML, research infrastructure, robotics, or similarly technical organizations; senior or staff-level judgment.
- Strong understanding of the machine learning development lifecycle, including datasets, model training, evaluation, iteration, and the practical challenges of moving models into production.
- Demonstrated ability to build an execution system from an ambiguous starting point, identify true critical dependencies, and drive progress across teams without direct reporting authority.
- Technical fluency sufficient to work credibly with researchers and infrastructure engineers, ask the right questions, and present real trade-offs—not just collect status.
- Experience coordinating constrained engineering resources, such as compute capacity, test systems, labs, hardware platforms, or specialized teams.
- Excellent written and verbal communication, including the ability to turn many threads of technical work into a concise, decision-ready view for leadership.
- Sound judgment about when to solve a coordination issue independently, when to involve technical owners, and when a decision needs leadership attention.

## Nice to have

- Experience in large-scale model training, foundation models, generative models, computer vision, embodied AI, or robotics.
- Familiarity with GPU clusters, data pipelines, robot testing and evaluation, or hardware/software integration.
- Experience bridging research organizations and customer-facing applied engineering or model release functions.

## Why this matters

Rhoda's capability roadmap spans faster task adaptation, instruction and demonstration following, higher execution speed, and dexterous manipulation. These breakthroughs depend on models, data, hardware, compute, and evaluation becoming ready in the right sequence. You'll help turn that complexity into a coherent execution engine—without slowing down the research itself. Success in this role means important handoffs are clear, blockers surface early, resource conflicts are resolved faster, technical teams spend less time coordinating across silos, and leadership has a trustworthy view of milestones and risks.

## About Rhoda AI

## Company Overview
- **One-liner**: Rhoda AI builds robot foundation models that learn from internet-scale video to enable manipulation-capable robots to generalize in real-world industrial environments.
- **Entity Type**: Private (Seed + Series A; $680M total funding)
- **Headquarters**: Palo Alto, CA, United States
- **Founded**: 2024
- **Founders**: Jagdeep Singh (CEO), Eric Chan (Chief Scientist), Changan Chen (Chief Research Officer), Andrew Wooten, Gordon Wetzstein (Scientific Advisor) [rhoda.ai/team](https://www.rhoda.ai/team)

## Core Business
- **Primary industry**: Robotics, Artificial Intelligence, Hardware
- **Target customers**: B2B – industrial enterprises in automotive, manufacturing, logistics, and e-commerce
- **Mission/purpose**: “Building at the frontier of embodied intelligence” and “Designing intelligence for the real world” – deploying general-purpose robot foundation models that adapt to the variability of commercial and industrial environments. [rhoda.ai](https://www.rhoda.ai/) | [linkedin.com](https://www.linkedin.com/company/rhoda-ai)

## Products & Services
- **Rhoda Robot Platform (Hardware + Software)**: A turnkey robotic system with custom actuators (25kg rated, 40kg peak payload), safety-rated vision, wheel-base, and brakes in every actuator. The platform runs the **Direct Video Action** model, which pre-trains on over a million real-world videos and post-trains on task-specific robot data. Long-context windows enable single-shot learning from human demonstrations without retraining. [rhoda.ai](https://www.rhoda.ai/)
- **FutureVision Intelligence Layer**: A proprietary architecture that handles real-world industrial tasks autonomously by generalizing beyond conventional VLA pipelines. [rhoda.ai](https://www.rhoda.ai/)
- **Deployment Services**: End-to-end solutions for tasks such as returns processing, bearing decanting, container breakdown, and material transport in logistics and e-commerce facilities. [rhoda.ai](https://www.rhoda.ai/)

## Market Standing
- **Valuation**: Not publicly disclosed
- **Key Metric**: Total funding **$680M** – Seed round $67.4M (April 2024), Series A $162.6M (April 2025), and Series A $450M (March 2026) with 4 investors. [linkedin.com](https://www.linkedin.com/company/rhoda-ai)
- **Notable Investors/Partners**: Not individually named in available sources; partners include customers in automotive, manufacturing, logistics, and e-commerce. [rhoda.ai](https://www.rhoda.ai/)
- **Growth Signals**: Headcount growth of **+20% monthly** (LinkedIn reports 55 employees; Built In reports 73 employees – conflicting data). Talent sourced from companies like QuantumScape, Flexiv Robotics, Scale AI, Google, Meta, NVIDIA, and Stanford University. [linkedin.com](https://www.linkedin.com/company/rhoda-ai) | [builtin.com](https://builtin.com/company/rhoda-ai)

## Competitive Advantages
- **Direct Video Action architecture** with web-scale video pre-training gives a strong prior on motion, physics, and dynamics, enabling generalization beyond lab settings.
- **Custom high-performance actuators** (25kg rated, 40kg peak) with safety-rated brakes and vision – designed for 3+ years of continuous operation at rated payload.
- **Long-context in-context learning** allows the robot to perform tasks single-shot from human demonstrations without retraining.
- **Turnkey industrial deployments** that handle ambiguity and variability (e.g., debris, transparent bags, heavy boxes) – tasks customers initially believed could not be automated. [rhoda.ai](https://www.rhoda.ai/)

## Strategic Focus
- Scaling robot intelligence through a pre-training/post-training paradigm, moving from controlled labs to reliable production environments.
- Expanding commercial deployments across automotive, manufacturing, logistics, and e-commerce verticals.
- Pursuing a path to **physical AGI** by combining foundation models with custom hardware for real-world adaptability. [rhoda.ai](https://www.rhoda.ai/)

## Why Work Here
- **Culture**: “Building at the frontier of embodied intelligence” – emphasis on hard problems, first-principles thinking, and category-defining systems. [linkedin.com](https://www.linkedin.com/company/rhoda-ai)
- **Work policy**: Hybrid workspace (employees combine remote and on-site work), with offices in Mountain View and Palo Alto, CA. [builtin.com](https://builtin.com/company/rhoda-ai)
- **Engineering culture**: Strong research focus (Chief Research Officer, Chief Scientist, many research engineers/scientists). Recent job postings include Research Scientist, Robot Perception Engineer, Mechanical Engineer, Fullstack Engineer, and Product Manager. [builtin.com](https://builtin.com/company/rhoda-ai)
- **Notable perks**: Not explicitly listed, but the company is well-funded ($680M) and at an early stage (founded 2024), offering significant growth opportunity and impact.

## Sources
1. [rhoda.ai](https://www.rhoda.ai/) – Company website (product, technology, commercial applications)
2. [rhoda.ai/careers](https://www.rhoda.ai/careers) – Careers page
3. [rhoda.ai/team](https://www.rhoda.ai/team) – Leadership team and co-founders
4. [builtin.com](https://builtin.com/company/rhoda-ai) – Built In profile (employee count, offices, job listings, hybrid policy)
5. [linkedin.com](https://www.linkedin.com/company/rhoda-ai) – LinkedIn company page (funding, headcount, executive list, talent sources)

## Other roles at Rhoda AI

- [Marketing Communications Senior Associate](https://feeny.ai/job/marketing-communications-senior-associate-rhoda-ai-mountain-view-vmkhppnjbaa4) — Mountain View, CA
- [Software Engineer, Rhoda Platform](https://feeny.ai/job/software-engineer-rhoda-platform-rhoda-ai-mountain-view-118z5qm9f5q0) — Mountain View, CA
- [Software Engineer Intern, Rhoda Platform](https://feeny.ai/job/software-engineer-intern-rhoda-platform-rhoda-ai-mountain-view-3s3s0rkqmbkw) — Mountain View, CA
- [Software Engineer Intern, Inference](https://feeny.ai/job/software-engineer-intern-inference-rhoda-ai-mountain-view-0yz1xmmcxnsq) — Mountain View, CA
- [Technical Program Manager](https://feeny.ai/job/technical-program-manager-rhoda-ai-mountain-view-1vmebb3sybwj) — Mountain View, CA
- [Solution Engineer](https://feeny.ai/job/solution-engineer-rhoda-ai-mountain-view-1fkt9bqkr8g7) — Mountain View, CA
- [Head of Talent](https://feeny.ai/job/head-of-talent-rhoda-ai-mountain-view-pt49x7f3hg0b) — Mountain View, CA
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- [Associate Engineering Product Manager- Robot Data Systems](https://feeny.ai/job/associate-engineering-product-manager-robot-data-systems-rhoda-ai-mountain-view-p6pw133hymk0) — Mountain View, CA
- [Research Member of Technical Staff- Training Systems](https://feeny.ai/job/research-member-of-technical-staff-training-systems-rhoda-ai-mountain-view-n7d7bvemaev0) — Mountain View, CA