Forward Deployed Engineer
San Francisco, CAFull-timePosted todayStill listed today
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Job overview
Reactor is building an inference platform for real-time world models. The Forward Deployed Engineer partners with model labs, visits their offices, and integrates models onto Reactor’s infrastructure for production-quality deployment. The role combines ML engineering and customer partnership, with responsibility for deployment, performance optimization, and product decisions shaped by partner needs. The engineer works directly with the founders and helps define forward deployment at Reactor.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Forward Deployed Engineer Department: Engineering Employment Type: Full Time Location: San Francisco
Description Reactor is building the inference platform for real-time world models. We run the largest and fastest catalog of world models on the market (15+ and growing), including LingBot World 2, LTX 2.5 Realtime, and HappyOyster. Our founders, Alberto Taiuti (CEO) and Bryce Schmidtchen (CTO), met as technical leads on the early Apple Vision Pro team. Alberto went on to co-found Luma AI, now a $4B company. We've raised $59M, led by Lightspeed, with Amplify Partners, WndrCo, and NVIDIA's NVentures participating. Jeffrey Katzenberg, cofounder of Dreamworks Animation, sits on our board of directors.
This role sits at the intersection of ML engineering and customer partnership. You will be the person who makes it real for our lab partners, going on-site to their offices, understanding their models deeply, and doing whatever it takes to get them running at production quality on Reactor's infrastructure.
This is not a support role. You will be making critical technical and product decisions and working directly with the founders. You will be one of the first people to define what forward deployment looks like at Reactor.
What You'll Do
- Travel to top world model labs, integrate their models onto Reactor's infrastructure, and own the deployment end to end
- Profile and optimize model performance to hit the latency and throughput targets that make real-time interactive video feel real
- Be the voice of the lab partner inside Reactor and make product decisions that directly shape what we build next
Who You Are
- 3+ years in ML engineering or a technical role working directly with external teams
- Comfortable reading and writing Python at a production level and tracing through inference pipelines to find and fix bottlenecks
- Strong knowledge of PyTorch and modern ML inference optimization techniques
- Comfortable with ambiguity, travel, and getting on a plane to unblock a partner
Nice to Have
- Experience with diffusion models, video generation, or world models
- Familiarity with real-time streaming systems
- CUDA kernel optimization, TensorRT, or custom inference frameworks
- Existing relationships in the generative video or foundation model ecosystem
Benefits
- Competitive SF salary and meaningful early equity
- Visa sponsorship and relocation support
- Generous health, dental, and vision coverage
- Travel covered for on-site integrations
How this job compares
Set against the 2,598 open Forward Deployed Engineer jobs on Olive Jobs, counted October 30, 2026.
- Pay
- This postingNot listed
- California median$154–260K/yr520 salary ranges
- US median$31–91/hr63 hourly ranges
- Openings
- Olive Jobs lists 630 open Forward Deployed Engineer jobs in California and 2,598 across the US. 6% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 3 years of experience; Forward Deployed Engineer postings that state a minimum ask for 5 years at the median (2,258 postings).
- Education
- 675 of the 2,598 open Forward Deployed Engineer jobs (26%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 30, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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