GTM Engineer

Applied Compute; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Competitive compensation and equity

100% employer-paid health insurance

Unlimited PTO

Paid parental leave

Daily lunches and dinners

Transportation and relocation support

401(k) with up to a 5% employer match

Job summary

Applied Compute is seeking a GTM Engineer in San Francisco to build production-grade software and LLM automations or to lead customer discovery and scoping for model post-training engagements. You’ll own end-to-end technical work and collaborate with our teams to align technical efforts with business outcomes.

The role emphasizes ownership, strong engineering foundations, and the ability to translate customer needs into scalable solutions.

Qualifications

• Prior professional experience as a software engineer or machine learning engineer, building and maintaining production systems on an engineering team.
• Strength in either building reliable software and LLM automations or leading technical discovery and scoping.
• Strong technical judgment, clear communication, and ownership from problem definition through execution.
• Nice to have: Ability to flex between coding and customer-facing work.

Responsibilities

• Build agents and automations for account intelligence, outbound, and GTM workflows.
• Build integrations across our CRM, communication tools, meeting transcripts, and external data sources so useful context reaches the right people.
• Take systems from initial idea through daily use, with testing, monitoring, and documentation that keep them reliable as the team scales.
• Lead discovery, qualify post-training opportunities, and define data, evaluation, and deployment requirements.
• Develop technical proposals and success criteria, answer customer questions, and coordinate handoffs to applied research engineers or our platform team.
• Explain our platform, recommend approaches, and address technical questions about model selection, training, inference, and integration.

Skills

Software engineering

ML engineering

LLM automation

Technical discovery

Customer-facing

Ownership

Communication

Job description

GTM Engineer

As a GTM Engineer at Applied Compute, you’ll specialize in one of two areas: building software and agent automations that help us find, win, and grow customer relationships, or leading customer discovery and use‑case scoping for model post‑training engagements. Your day‑to‑day responsibilities will center on one primary focus, based on your strengths and the team’s needs.

Both focus areas call for a strong engineering foundation, ownership, and an ability to connect technical work to customer and business needs.

Responsibilities

The following responsibilities correspond to the specialization area you fit into

Coding and automation

• Build agents and automations for account intelligence, outbound, and GTM workflows

• Build integrations across our CRM, communication tools, meeting transcripts, and external data sources so useful context reaches the right people

• Take systems from initial idea through daily use, with testing, monitoring, and documentation that keep them reliable as the team scales

Customer discovery and scoping

• Lead discovery, qualify post‑training opportunities, and define data, evaluation, and deployment requirements

• Develop technical proposals and success criteria, answer customer questions, and coordinate handoffs to applied research engineers or our platform team

• Explain our platform, recommend approaches, and address technical questions about model selection, training, inference, and integration

Qualifications

• Prior professional experience as a software engineer or machine learning engineer, building and maintaining production systems on an engineering team

• Strength in either building reliable software and LLM automations or leading technical discovery and scoping

• Strong technical judgment, clear communication, and ownership from problem definition through execution

• Nice to have: Ability to flex between coding and customer‑facing work

About us

Applied Compute builds Specific Intelligence for the enterprise. We provide the infrastructure and expertise for companies to post‑train and serve open‑weight models tailored to their proprietary data, institutional knowledge, and workflows. Our researchers and applied AI team work directly with customers to define evaluations, train models, and improve performance on the tasks that matter to their business.

Why we’re excited:

Our product team builds the platform for model training and inference. Our research team pushes the frontier of post‑training and reinforcement learning. Our applied AI team works side‑by‑side with customers to turn model improvements into production results. This combination of strong product, deep research, and hands‑on customer work is what we believe it takes to bring AI to the enterprise. We are product‑led, research‑enabled, and forward‑deployed.

Who we are:

We’re a team of engineers, researchers, and operators. Many of us are former founders. We’ve built RL infrastructure at OpenAI, data foundations at Scale AI, and systems at Together, Two Sigma, Watershed, and others. We work with F50 customers and are fortunate to be backed by partners like Kleiner Perkins, Benchmark, Sequoia, Lux, and Greenoaks.

Who thrives here:

We’re looking for people who are excited about applying novel research and complex systems to real‑world problems. Our team enjoys working with customers: listening, empathizing, and understanding how work actually gets done in their organisations.

Benefits & Logistics

This role is based in San Francisco. We work from our office in the Mission. We offer:

• Competitive compensation and equity

• 100% employer-paid health insurance coverage

• Unlimited PTO

• Paid parental leave

• Daily lunches and dinners

• Transportation and relocation support

• 401(k) with up to a 5% employer match

As set forth in Applied Compute’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.