> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt. # Applied Researcher - Forward-Deployed RL Canonical URL: https://nextmove.md/fde/jobs/0ed15e783d00992e Prime Intellect posts a FDE role to build what the customer runs in San Francisco, CA and 1 more, at $150,000–$300,000 base, above the senior FDE median of $190,000 across 1,849 postings with pay. Own externally facing applied RL programs end to end, translating customer workflows into environments, evaluations, post-training experiments, and deployed improvements. Read from the employer’s posting on November 6, 2026. - [Prime Intellect](https://nextmove.md/fde/companies/prime-intellect) Posted Oct 19, 2026 by Prime Intellect · open on Ashby as of Nov 6, 2026 **$150,000–$300,000** + equity San Francisco, CA +1 Remote Full-time Own externally facing applied RL programs end to end, translating customer workflows into environments, evaluations, post-training experiments, and deployed improvements. - [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F0ed15e783d00992e&placement=top) - [View posting at Prime Intellect](https://jobs.ashbyhq.com/PrimeIntellect/af2f419f-6596-4805-8e83-9cee5016aa1a/application) Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so. ## At a glance ### Posted base pay $150K–$300K Above the median Midpoint $225K · median $190K This job $150K to $300K. Senior FDE postings, 1,849 postings: the middle 50% of posted pay is $160K to $220K, median $190K. ### The work Builds what the customer runs Balance **Mostly building** Project stages 1. Pre-sales (not covered) 2. Proof of concept (not covered) 3. Implementation 4. Operations - **Coding**: Writes production code - **Builds for**: Both - **Level**: Senior - **Role**: Individual contributor ### What they ask for Visa - **Sponsors visas** ### Do you meet what the posting states? The posting reads as a senior role. What level are you at now? The work is remote from the US. Can you work from the US? Which of these have you used in production? Answer each one. Nothing is saved or sent. [What postings ask for, by background →](https://nextmove.md/fde/paths) ## Conditions - **Location**: San Francisco, CA · New York, NY - **Work arrangement**: Remote - **Remote work restrictions**: Flexible work: San Francisco, New York, London, or remote. - **Employment type**: Full-time - **Visa sponsorship**: Available - **Pay**: ## More like this [6sense](https://nextmove.md/fde/companies/6sense) ### [Sr. ML Ops Engineer, Forward-Deployed ](https://nextmove.md/fde/jobs/06ba4bd7675e00f2) San Francisco, CA Remote 11d ago $191,475–$260,830 [Databricks](https://nextmove.md/fde/companies/databricks) ### [Sr. Forward Deployed Engineer - Public Sector](https://nextmove.md/fde/jobs/440870dea6def209) Berkeley, CA · Kansas City, MO · +1 more Remote New · 2d ago $182,000–$250,208 [Roboflow](https://nextmove.md/fde/companies/roboflow) ### [Forward Deployed Engineer](https://nextmove.md/fde/jobs/d8c0abf8214d490b) New York, NY · San Francisco, CA Remote 5mo ago $180,000–$250,000 ## The job description from Prime Intellect Posted by Prime Intellect on Oct 19, 2026 ### Own Your Intelligence Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own. Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet. ### Role Impact You will own applied RL programs from the first ambiguous customer problem through a deployed improvement loop. You will understand the workflow and business stakes, decide what can be measured and learned, build the environment and evaluation, run post-training experiments, deploy the result, and determine what should generalize into Prime's shared stack. The majority of your work will be organized around external programs. You will work directly with customer researchers, engineers, and leaders, and you will be accountable for both the research result and its practical impact. ### Responsibilities ### Applied Research at Prime We turn a workflow into tasks, environments, evaluations, and reward signals, run post-training experiments against real baselines, and deploy what works. When a result looks good, we find out whether the gain came from the model or from the data, harness, inference, or infrastructure. The reusable parts become shared research, open-source systems, and product capabilities. Every Applied Research role is externally facing. Most researchers work directly with customers, users, or research partners while maintaining a substantive research agenda. ### Role scope We have active programs across technology, science, engineering, regulated industries, and the public sector. ### Representative early problems - Turn a partially documented workflow and business goal into an environment, baseline, and evaluation that the customer team agrees measures the right outcome. - Improve a domain agent through RL or another post-training method while separating model limitations from task, harness, inference, and integration failures. - Carry a successful experiment into deployment, measure its effect on the customer outcome, and convert the recurring parts into reusable environments, recipes, data loops, or platform capabilities. ### What you will own - Technical and business discovery that produces a clear research plan, success measure, environment, and baseline. - RL, distillation, and other post-training experiments tied to deployment outcomes. - Agent systems that handle tool use, memory, recovery, long horizons, and human oversight. - Deployment and adoption decisions, plus reusable artifacts carried back to Prime's research, engineering, and product teams. ### Requirements - Relevant experience: customer-embedded technical work, research engineering, technical founding experience, applied ML consulting with real build ownership, or end-to-end post-training programs. - You should be comfortable with senior external teams and able to connect experimental evidence to business decisions without lowering the research bar. - Hands-on experience building and debugging model-training, post-training, agent, evaluation, or closely adjacent experimental loops. - Strong experimental judgment: meaningful baselines, careful trace inspection, clear failure attribution, and a willingness to change direction when the evidence changes. - Strong Python and the ability to build artifacts that other researchers and engineers can run, inspect, and extend. - Comfort owning ambiguous problems and keeping partners and teammates current as you resolve them. ### Evidence of exceptional work We value publications, open-source systems, benchmarks, and shipped products as evidence of exceptional work. Show us something difficult you built, what failed, and how the evidence changed your approach. ### Benefits and Perks - Cash Compensation Range of $150-300k + equity incentives - Flexible Work (San Francisco, New York, London, or remote) - Visa Sponsorship & relocation support - Professional Development budget - Team Off-sites & conference attendance If you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you. [View posting at Prime Intellect](https://jobs.ashbyhq.com/PrimeIntellect/af2f419f-6596-4805-8e83-9cee5016aa1a/application) ## About Prime Intellect Full-stack platform and open research lab providing compute, reinforcement-learning training, environments, sandboxes, evaluations, inference, and deployment so companies can train and continuously improve agentic models. 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