---
title: 'Applied Researcher - Deployment Intelligence & Continuous Learning at Dyna Robotics'
canonical: 'https://feeny.ai/job/applied-researcher-deployment-intelligence-continuous-learning-dyna-robotics-2vv1eskyg11k'
type: 'job'
last_seen: '2026-09-06'
---

# Applied Researcher - Deployment Intelligence & Continuous Learning at Dyna Robotics

- **Company:** Dyna Robotics
- **Location:** Redwood City, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-21
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/dyna-robotics/09648521-c515-4e1d-a00d-92644b554d0a

## Job description

Dyna Robotics builds general-purpose robots powered by a proprietary embodied AI foundation model with top-in-industry generalization and real-world performance. Already deployed with customers across multiple industries, our robots do commercial-grade work in the physical world. Our team comes from Google DeepMind, Meta, and Cruise, and we're backed by CRV, First Round, and other leading investors.

## THE ROLE

Our models don't stop learning at deployment. A growing fleet of robots is generating real production data every day, and the gap between "works in the lab" and "works at a new customer site, forever" is a research problem, not just an ops one. As an Applied Researcher on the AI Research team, you'll own that gap: mining fleet sensor and video data for failure modes, building the monitoring that catches problems before customers do, and turning deployment data into continuous, measurable model improvement. This is a hands-on, ship-it role. We care far more about whether you can land a real improvement on the fleet than about producing research for its own sake.

## WHAT YOU'LL DO

- Continuous Learning Loops: Design and ship pipelines that turn real deployment data (successes, failures, teleop corrections) into targeted fine-tuning and online policy improvement, closing the loop from field to model without a full retrain cycle every time.
- Fleet Data Analytics: Mine high-frequency multimodal sensor and video data across tens of thousands of fleet episodes to catch failure modes, drift, and regressions before they become customer-visible.
- RL for Deployment: Apply reinforcement learning (offline RL, RL fine-tuning, reward modeling from human and teleop feedback) to improve policies directly from real-world deployment data, not just simulation.
- Automated Fleet Monitoring: Build automated monitoring that flags anomalies, near-failures, and out-of-distribution scenes across the fleet in real time, and that decides what needs a human versus what the system can self-correct.
- Cross-Scene Generalization: Characterize and close generalization gaps as robots move to new sites, lighting, layouts, and objects; build the evaluation harnesses and data-selection strategies that make day-one performance at a new customer site predictable.
- End-to-End Ownership: Partner with Research, Data, and Deployment teams to turn a finding into a shipped improvement, from a data-analysis notebook to a production monitoring dashboard to a deployed model update.

## WHAT YOU'LL BRING

- Bias to Ship: You're happiest closing the loop, landing a fix on the fleet and watching it hold up at a real customer site, rather than polishing a benchmark number or a paper. We want someone driven by shipped impact and genuine passion for the problem, not research for its own sake.
- Educational Background: Bachelor's, Master's, or PhD in CS, Robotics, Statistics, or a related field, or equivalent practical experience. Degree level doesn't matter to us; what matters is genuine passion for the work and a track record of hands-on effort that shipped into a real system, not just a benchmark.
- Applied ML Depth: Hands-on experience in at least two of: reinforcement learning, sensor-data modeling/anomaly detection, vision-language models, or continual/online learning.
- Production Instincts: Experience building monitoring, evaluation, or data pipelines for a live ML system, comfortable with the ambiguity of real-world fleet data versus curated benchmarks.
- Experimentation & Statistics: Comfortable designing and reading production experiments (A/B tests, canary rollouts, staged fleet deployments) and applying enough statistical rigor to tell a real regression from noise in messy real-world data.
- Technical Stack: Strong Python and PyTorch (or JAX); comfortable with large multimodal datasets and distributed compute (Slurm/GPU clusters).
- Communication: Able to turn a fleet-scale data investigation into a clear recommendation that researchers and operators can act on.

## BONUS POINTS FOR

- Experience with robot fleets or other physically-deployed autonomous systems in the field, not just simulation.
- Experience building or fine-tuning perception or foundation models for automated monitoring, captioning, or anomaly detection.
- Background in statistical methods for detecting anomalies and drift (change-point detection, forecasting) applied to sensor or telemetry data.
- Experience with human-in-the-loop learning: reward modeling from operator corrections, active learning, or data curation from failure cases.

At Dyna Robotics, we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect.

Don’t let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you’re passionate about robotics, no matter your discipline, we want to hear from you, even if you don't check every box.

## About Dyna Robotics

## Company Overview
- **One-liner**: Dyna Robotics builds general-purpose commercial robots powered by proprietary embodied AI foundation models that achieve human-level dexterity and self-improvement across diverse real-world environments.
- **Entity Type**: Private (Series A)
- **Headquarters**: Redwood City, California, United States
- **Founded**: 2024
- **Founders**: Lindon Gao (CEO), York Yang (Co‑founder), Jason Ma (Co‑founder / former DeepMind research scientist)

## Core Business
- **Primary industry**: Robotics / Artificial Intelligence (embodied AI foundation models)
- **Target customers**: B2B – enterprises in manufacturing, logistics, laundry, food service, hospitality, and other industries requiring repetitive manipulation tasks
- **Mission statement**: “To empower businesses by automating repetitive, stationary tasks with affordable, intelligent robotic arms. Driving the future of general‑purpose robotics—one manipulation skill at a time.” [builtin.com](https://builtin.com/company/dyna-robotics)

## Products & Services
- **DYNA‑1 Foundation Model** – A single‑weight, general‑purpose vision‑language‑action (VLA) model that achieves 99%+ success rates in 24‑hour non‑stop operation. It generalizes zero‑shot to unseen environments and learns new skills within hours. [dyna.co](https://www.dyna.co/)
- **DYNA‑1i: Open‑World Dexterity** – Production‑grade manipulation system with real‑time self‑correction and human‑level dexterity at commercial throughput. [dyna.co](https://www.dyna.co/)
- **Factory Automation** – 24/7 autonomous operation for precision manufacturing, kitting, assembly, pick‑and‑place, quality inspection, and packaging.
- **Laundry & Garment** – Automated folding and garment handling (e.g., DYNA‑1 folds 40+ shirts per hour).
- **Food & Hospitality** – Food service automation including napkin folding, plating, and delicate manipulation tasks.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metrics**:
  - **Total Funding**: $143.5 M (Seed $23.5 M in March 2025; Series A $120 M in September 2025) [prnewswire.com](https://www.prnewswire.com/news-releases/dyna-robotics-raises-120-million-to-advance-robotic-foundation-models-on-the-path-to-physical-artificial-general-intelligence-302556817.html)
  - **Employees**: 98 (as of mid‑2025), +213.9% YoY headcount growth [linkedin.com](https://www.linkedin.com/company/dyna-robotics)
- **Notable Investors/Partners**: CRV, RoboStrategy, First Round Capital, Salesforce Ventures, NVentures (NVIDIA), Amazon Industrial Innovation Fund, Samsung Next, LG Technology Ventures.
- **Growth Signals**:
  - Robots already deployed 16 hours/day at hotels, restaurants, laundromats, and gyms within six months of launch.
  - Strong talent influx from Tesla (14 employees), Cruise, Meta, Nuro, Amazon Lab126.
  - LinkedIn follower growth +404.3% year‑over‑year.

## Competitive Advantages
- **First general‑purpose foundation model for robotics** that works out‑of‑the‑box in new environments without custom engineering.
- **99%+ success rate** in continuous 24‑hour operation and ability to self‑improve through on‑the‑job data.
- **Rapid learning**: new skills acquired in hours, not weeks, with fleet‑wide updates.
- **Founding team** with proven exit (Caper AI sold for $350 M) and deep research pedigree (DeepMind).

## Strategic Focus
- Expand world‑class research and engineering team.
- Accelerate development of next‑generation foundation model.
- Scale commercial deployments across manufacturing, hospitality, and service industries.
- Collect high‑quality data from real‑world customers to continuously improve model generalization.

## Why Work Here
- **In‑office culture** – All employees work from physical offices in Redwood City, CA (with small satellite presence in China, Canada, Hong Kong). Strong in‑person collaboration is emphasized. [builtin.com](https://builtin.com/company/dyna-robotics)
- **Engineering‑heavy environment** – 27% of staff in technical roles, 9% in research, and 5% consulting. Recent open roles include Deployment Engineer, Research Engineer/Scientist, Full‑Stack Robotics Software Engineer, and Data Infra Engineer.
- **High growth trajectory** – Headcount nearly tripled in a year, with aggressive hiring across operations, research, and product.
- **Impactful mission** – Opportunity to work on cutting‑edge embodied AI that directly automates physical tasks, with a path toward physical AGI.
- **Competitive compensation & perks** (inferred from top VC backing and talent drawn from Big Tech).

## Sources
1. [dyna.co](https://www.dyna.co/) – Official website
2. [builtin.com](https://builtin.com/company/dyna-robotics) – Company overview, jobs, culture
3. [linkedin.com](https://www.linkedin.com/company/dyna-robotics) – Company details, funding, employee growth
4. [prnewswire.com](https://www.prnewswire.com/news-releases/dyna-robotics-raises-120-million-to-advance-robotic-foundation-models-on-the-path-to-physical-artificial-general-intelligence-302556817.html) – Series A announcement

## Other roles at Dyna Robotics

- [HR Business Partner](https://feeny.ai/job/hr-business-partner-dyna-robotics-redwood-city-xbs5vdzs7xqs) — Redwood City, CA
- [Exceptional Software Engineer](https://feeny.ai/job/exceptional-software-engineer-dyna-robotics-redwood-city-5emz05d1phvm) — Redwood City, CA
- [Video Producer & Editor](https://feeny.ai/job/video-producer-editor-dyna-robotics-redwood-city-88azpea4dg8x) — Redwood City, CA
- [Product Manager, Data Engine](https://feeny.ai/job/product-manager-data-engine-dyna-robotics-redwood-city-k3w3we7tktyy) — Redwood City, CA
- [Robotics Hardware Reliability Engineer](https://feeny.ai/job/robotics-hardware-reliability-engineer-dyna-robotics-redwood-city-ca3qm930xv29) — Redwood City, CA
- [Annotation Operations Manager](https://feeny.ai/job/annotation-operations-manager-dyna-robotics-redwood-city-edm60c94sdh0) — Redwood City, CA
- [Research Engineer/Scientist, Simulation](https://feeny.ai/job/research-engineer-scientist-simulation-dyna-robotics-redwood-city-kbtftjmb38vj) — Redwood City, CA
- [Robot Safety Operator - Walnut Creek, CA](https://feeny.ai/job/robot-safety-operator-walnut-creek-ca-dyna-robotics-customer-site-k214rxsy0czt) — Customer Site
- [Operations Recruiter](https://feeny.ai/job/operations-recruiter-dyna-robotics-redwood-city-ygjfchdarmwj) — Redwood City, CA
- [Robot Safety Operator - San Diego](https://feeny.ai/job/robot-safety-operator-san-diego-dyna-robotics-customer-site-3rtaadtd0p57) — Customer Site