---
title: 'Research Technician — Autonomous Platform (Nights / Weekends) at Medra'
canonical: 'https://feeny.ai/job/research-technician-autonomous-platform-nights-weekends-medra-san-francisco-1d3pkp31a1hc'
type: 'job'
last_seen: '2026-09-08'
---

# Research Technician — Autonomous Platform (Nights / Weekends) at Medra

- **Company:** Medra
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-08-18
- **Last confirmed live:** 2026-09-08
- **Apply:** https://jobs.ashbyhq.com/medraai/7b2fba8b-4074-4a38-9453-1ff9ef6ee259

## Job description

## What We're Building

At Medra, our mission is to use AI, robotics, and biology to accelerate life science research, with the ultimate goal of eradicating disease. We have been quietly building the foundational layers of our Physical AI Scientist platform:

- 🤖 Physical AI that can operate scientific instruments with human-level dexterity.
- 🧪 Scientific AI that can analyze results, reason about next steps, and close the loop autonomously.

This is an incredibly ambitious mission, but we believe that a team of ambitious people with high ownership can accomplish incredible things.

We're looking for a hands-on Research Technician to keep our autonomous platform running on nights and/or weekends. Our robots don't sleep, and this role is the human hands and eyes that keep our antibody screening workflow moving when the rest of the team is offline. You don't need to know every technique on day one — you need to be meticulous, dependable, and genuinely excited to learn the whole stack on the job.

## What You'll Do

- Run scheduled experiments, monitor automated runs in progress, and keep the platform loaded, supplied, and productive so it never sits idle
- Support our antibody screening workflow end to end — construct prep and assembly PCR, protein production of VHH/scFv/Fc-fusion binders, bead-based cleanup, and column purification
- Operate liquid handlers, magnetic particle processors (e.g., KingFisher), and plate-based workstations: load decks, launch methods, and recover from routine errors
- Set up and monitor SPR/BLI kinetics and quantitation runs (e.g., Carterra, Gator), HPLC-based purity/analytical QC, and sample QC (e.g., NanoDrop), flagging off-spec results
- Support mammalian cell culture (e.g., CHO) and cell-based assays — PD-L1 binding/blocking, flow cytometry sample prep — keeping cells and assay plates on schedule
- Follow SOPs precisely, capture clean data and metadata, and package results so the platform and the day team can pick up seamlessly
- Keep the lab shift-ready: restock consumables, manage sample chain-of-custody, follow BSL-2 and EHS practices, and leave clear handoff notes

## What You Bring to the Team

- Associate's or Bachelor's degree in a scientific field with hands-on lab experience
- Some wet-lab experience and real comfort at the bench — careful pipetting, following protocols, and keeping rigorous records
- Availability to work night and/or weekend shifts on a regular basis
- Exceptional attention to detail and reliable follow-through; you run the same step the same way every time and notice when something looks off
- A fast learner with a scrappy, can-do attitude who wants to master an unfamiliar, multi-step workflow rather than stay in one narrow task
- Comfort working independently and troubleshooting calmly, with good judgment on when to escalate
- Genuine enthusiasm for automation and robotics — you're excited to work alongside machines

Bonus Points For

- Hands-on experience with any part of the antibody stack: protein expression, IMAC/affinity purification, HPLC, or biophysical binding assays (SPR/BLI)
- Mammalian cell culture, cell-based assays, or flow cytometry experience
- Experience operating liquid handlers, plate readers, or robotic workstations
- Comfort with data tools or LIMS/ELN platforms (e.g., Benchling)

This position is 100% in-person; you must be able to come on-site to our San Francisco office.

## What We Offer

- An opportunity to change the way that scientific research happens
- Fast-paced, creative, and collaborative work environment
- Significant equity ownership
- 401k
- Medical and dental insurance
- Unlimited PTO
- Weekday dinners

## About Medra

## Company Overview
- **One-liner**: Building autonomous Physical AI for the lab to accelerate scientific discovery by executing and optimizing experiments in a closed loop.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States (340 Pine Street, Suite 100)
- **Founded**: 2021 (some sources cite 2022 – conflicting reports)
- **Founders**: Michelle Lee (CEO)

## Core Business
- **Primary industries**: Life sciences automation, laboratory robotics, AI-driven experimental design
- **Target customers**: B2B – biopharma companies, academic research labs, government agencies (e.g., DARPA)
- **Mission / purpose**: Unlock breakthroughs at scale by tightly integrating AI scientific reasoning with physical experimentation.

## Products & Services
- **Physical AI Lab (Medra Lab 001 – ML001)**: A fully autonomous robotic workcell that executes wet-lab protocols (e.g., CRISPR, cell culture, NGS) using computer vision and robotic manipulation. Instrument-agnostic and modular.
- **AI Experimentalist**: The scientific reasoning layer that translates natural-language research goals into executable experiment plans, coordinates multi-step protocols, analyzes results, and refines methods in a closed loop.
- **Platform Type**: Physical AI + Scientific AI as a service (on-site deployment or remote operation via ML001).

## Market Standing
- **Valuation / Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding of $63M (Series A of $52M closed December 2025, preceded by $11M pre-seed in October 2025 and a non-equity assistance from PharmStars in 2023)
- **Notable Investors / Partners**: Human Capital (lead), Lux Capital, Menlo Ventures, Catalio Capital, Neo, 776 (Seven Seven Six), Fusion Fund, Nat Friedman & Daniel Gross
- **Growth Signals**:
  - Headcount grew 100% YoY (31 employees as of mid-2026)
  - Launched ML001 in San Francisco (April 2026) — largest autonomous lab in the U.S.
  - Announced DARPA collaboration (June 2026) to advance natural-language-to-executable-experiment capabilities
  - 8 open positions across biology, engineering, design, and operations

## Competitive Advantages
- **Closed-loop integration**: Combines physical execution with AI-driven experimental design and learning – not just robotic task automation.
- **Instrument-agnostic & modular**: Works with both manual and automated lab instruments, allowing easy swapping of modules and protocols.
- **Natural-language programming**: Scientists can edit protocols in plain English (written or voice).
- **Scalable data generation**: Logs every action, video, and metadata per sample for traceability and model training.

## Strategic Focus
- Expand partnerships with biopharma, academia, and government (DARPA is a key early customer).
- Advance the AI Experimentalist layer to enable full autonomous hypothesis generation and validation.
- Scale deployments of Physical AI Labs on-site and remotely through ML001.

## Why Work Here
- **Culture**: Described as “intense curiosity and rigorous debate” with clear, direct communication and quick resolution of conflicts through mutual respect.
- **Team**: Community of diverse thinkers, “not just a company but a movement to transform biotechnology.”
- **Work policy**: Likely on-site at the San Francisco lab given the nature of physical robotics; no explicit remote/hybrid policy mentioned.
- **Perks & highlights**: Opportunity to work on cutting-edge AI + robotics with a high-impact mission; funded by top-tier VCs; strong engineering culture (43% technical staff, many from Neuralink, Applied Intuition, Amazon, Carnegie Mellon).

## Sources
1. [medra.ai](https://www.medra.ai/)
2. [medra.ai/careers](https://www.medra.ai/careers)
3. [linkedin.com/company/medra-ai](https://www.linkedin.com/company/medra-ai)
4. [cbinsights.com/company/medra](https://www.cbinsights.com/company/medra)
5. [medra.ai/darpa-collaboration](https://www.medra.ai/darpa-collaboration)
6. [jobs.ashbyhq.com/medraai](https://jobs.ashbyhq.com/medraai)

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