> 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.

# MTS, Post-Training (Enterprise)

Canonical URL: https://nextmove.md/fde/jobs/96da9294487106dd

Bespoke Labs posts a FDE role to build what the customer runs in Mountain View, CA and 1 more, at $300,000–$350,000 base, above the senior FDE median of $190,000 across 1,864 postings with pay. Delivery-focused post-training role responsible for shipping custom, production-ready models to 2–3 enterprise customers by year-end. Read from the employer’s posting on November 8, 2026.

- [Bespoke Labs](https://nextmove.md/fde/companies/bespoke-labs)

Posted Sep 29, 2026 by Bespoke Labs · open on Ashby as of Nov 8, 2026

**$300,000–$350,000** Mountain View, CA +1 On-site Full-time

Delivery-focused post-training role responsible for shipping custom, production-ready models to 2–3 enterprise customers by year-end.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F96da9294487106dd&placement=top)
- [View posting at Bespoke Labs](https://jobs.ashbyhq.com/bespokelabs/68f40af2-e6a4-4b25-9263-3463d4e87cd4/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

$300K–$350K Above the median

Midpoint $325K · median $190K

This job $300K to $350K. Senior FDE postings, 1,864 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**: External customers

- **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 job is in Mountain View, CA · San Francisco, CA. Could you work in one of these?

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**: Mountain View, CA · San Francisco, CA

- **Work arrangement**: On-site

- **Remote work restrictions**: Mountain View, CA preferred or San Francisco, CA onsite; remote considered.

- **Employment type**: Full-time

- **Visa sponsorship**: Available

- **Pay**:

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## The job description from Bespoke Labs

Posted by Bespoke Labs on Sep 29, 2026

### About Bespoke Labs

Bespoke Labs is an applied AI research lab pioneering data and RL environment curation for training and evaluating agents.

Recently, we curated Open Thoughts, one of the best open reasoning datasets used by multiple frontier labs, trained SOTA specialized models such as Bespoke-MiniChart-7B and Bespoke-MiniCheck, and taught agents to do multi-turn tool-calling with reinforcement learning.

Bespoke is uniquely positioned to capture a large market share of data and RL environment curation.

### About the Role

This is a delivery-heavy role focused on standing up our enterprise post-training capability. Demand is inbound, and our goal is to ship custom, high-performing models to 2–3 paying enterprise customers by year-end. Over the first 6–12 months, you will do the execution work required to solve real-world enterprise problems while helping build the scalable product underneath.

You will not be running abstract experiments or training models solely for benchmarks. You will sit directly at the intersection of enterprise demand and applied post-training—curating data, building rigorous eval suites, fine-tuning models, and proving their value to enterprise stakeholders. We will measure you on the production impact, robustness, and delivery of models shipped to real users, not on published papers.

The thing we care about most is whether you have done this before. If you have post-trained an LLM, shipped it to production users, managed regression risks, and owned the evals from end-to-end, we want to talk.

### What You'll Do

- **Ship enterprise-grade models.** Post-train, fine-tune, and align open-weight and proprietary base models for complex business domains, ensuring they perform reliably in production.
- **Build bespoke evaluation suites.** Define what "quality" means for subjective domain-specific tasks, create custom benchmarks, and calibrate LLM judges against human domain experts.
- **Curate and filter high-impact datasets.** Build and run production data flywheels combining real production traces, human labeling, and synthetic augmentation with strict filtering standards.
- **Manage and mitigate regression risk.** Rigorously track downstream performance to ensure fine-tuning for new behaviors doesn't silently degrade core capabilities or reasoning.
- **Engage directly with stakeholders.** Sit in front of product and enterprise customers to understand their requirements, translate vague domain preferences into technical eval metrics, and explain model behavior clearly.
- **Deploy for cost and privacy.** Fine-tune open-weight architectures (e.g., Llama, Qwen, Mistral, DeepSeek) to hit strict enterprise latency, cost, and privacy targets.
- **Direct frontier tools and workflows.** Leverage state-of-the-art post-training techniques, preference tuning, and data curation tooling to maximize output quality and delivery speed.

### What We're Looking For

- **A record of shipped models.** You have post-trained at least one LLM that was deployed to real users in production, and you can show how you measured its success.
- **End-to-end eval ownership.** Demonstrated experience building benchmarks, creating eval datasets, and getting stakeholders to agree on clear metrics for complex or subjective tasks.
- **Deep understanding of regression risks.** You can instinctively explain how training a model on new behaviors impacts existing capabilities and how to prevent it.
- **Customer-facing or product empathy.** Experience collaborating directly with non-ML stakeholders, enterprise customers, or product managers to turn requirements into model behavior.
- **Strong software and ML fundamentals.** Fluency in modern post-training frameworks, data processing pipelines, and code bases designed for production deployment.
- **Ownership mindset.** You take complete responsibility for the full post-training lifecycle—from raw data to model deployment and failure analysis—without requiring close supervision.

### You May Be a Good Fit If You Also

- Have post-trained conversational or task-oriented assistants (e.g., support agents, multi-turn chat, tool-using agents)
- Have built LLM judges or reward models and calibrated them against human raters
- Have operated a production data flywheel: traces → labeling → synthetic augmentation → retrain
- Have extensive hands-on experience with open-weight models (Llama, Qwen, Mistral, DeepSeek) for cost, latency, or privacy optimization
- Come from forward-deployed engineer (FDE), founder, or early-stage startup backgrounds

### What We Offer

- **Location:** Mountain View, CA (Preferred) or San Francisco, CA (Onsite); Remote considered
- **Base Salary:** $300,000 – $350,000 USD / year
- **Additional Comp:** 25% performance-based bonus + equity

### Benefits & Perks

- Health, dental, and vision coverage
- 401(k)
- Daily onsite lunch provided
- Visa sponsorship and relocation support available
- Direct impact on how the industry trains and evaluates agents

We value different backgrounds and paths into this work. If this role excites you but you do not check every box, apply anyway.

[View posting at Bespoke Labs](https://jobs.ashbyhq.com/bespokelabs/68f40af2-e6a4-4b25-9263-3463d4e87cd4/application)

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