Forward Deployed Engineer

fastino.ai; Oregon; Hybrid; USD 140,000 - 220,000; Full time

Job summary

Fastino is seeking a Forward Deployed Engineer to sit inside customer stacks in San Francisco and drive production-grade ML deployments. You will own technical engagements from first call to go-live, writing integrations, data pipelines, and eval harnesses that run on customer infra.

You will fine-tune models, compare against baselines for accuracy, latency, and cost, and debug complex issues across auth, networking, GPU, and security. Travel to customer sites is expected.

Qualifications

• BS or MS in CS or equivalent experience.
• 3+ years as software engineer, customer-facing preferred.
• Strong Python and at least one of TS/Go/Rust.
• Experience shipping LLM/ML systems to production.
• Cloud and infra basics: AWS/GCP/Azure, Docker, Kubernetes, networking, security.
• Able to explain tradeoffs to engineers and executives.
• Ownership mindset; fix it instead of filing tickets.
• Bonus: GLiNER/NER or information extraction.
• Bonus: startup experience.
• Willing to travel to customer sites.

Responsibilities

• Embed with customer teams to scope, build, and deploy Fastino models into production systems.
• Write code: integrations, data pipelines, eval harnesses, and services that run on customer infra (cloud, VPC, on prem).
• Fine-tune and evaluate models on customer data and beat baseline on accuracy, latency, and cost.
• Debug authentication, networking, GPU/inference performance, data quality, edge cases.

Skills

Python

TypeScript

Go

Rust

LLM/ML production

Cloud basics

Docker

Kubernetes

Networking & security

Communicating tradeoffs

Ownership mindset

GLiNER/NER or info extraction

Startup experience

Travel to customer sites

Education

BS in Computer Science

MS in Computer Science

Equivalent experience

Tools

AWS

GCP

Azure

Job description

Forward Deployed EngineerFull-time | San Francisco

About Fastino

• We're building specialized, efficient language models that beat big general models on the tasks that matter. Our team includes alumni from Google Research, Apple, Stanford, and Cambridge.
• Our open source GLiNER models have been downloaded 50M+ times and are used by teams at NVIDIA, Meta, and Airbnb.
• We've raised $25M (covered in TechCrunch) from Microsoft, Khosla Ventures, Insight Partners, GitHub CEO Thomas Dohmke, Docker CEO Scott Johnston, and others.

The Role

You’ll be the engineer who sits inside our customers’ stacks and gets them running in production. If you like hard technical problems and talking to the people who have them, this is for you.

What You’ll Work On

• Embed with customer engineering teams to scope, build, and deploy Fastino models into their production systems.
• Write real code: integrations, data pipelines, eval harnesses, and services that run on customer infra (cloud, VPC, on prem).
• Fine-tune and evaluate models on customer data, and prove they beat the baseline on accuracy, latency, and cost.
• Debug the messy stuff: auth, networking, GPU and inference performance, data quality, weird edge cases.
• Own the technical side of deals from first call through go-live, working closely with our founders and AEs.
• Turn what you build in the field into reusable tools, reference architectures, and SDK improvements.
• Bring customer feedback straight to research and product, and push for what customers actually need.

What We’re Looking For

• BS or MS in Computer Science or a related field (or equivalent experience).
• 3+ years as a software engineer, ideally with some time in a customer facing role (FDE, solutions engineering, consulting, or similar).
• Strong in Python. Comfortable with at least one of TypeScript, Go, or Rust.
• Hands on experience shipping LLM or ML systems to production: APIs, fine-tuning, evals, RAG, or agents.
• Solid with cloud and infra basics: AWS/GCP/Azure, Docker, Kubernetes, networking, and security.
• Clear communicator who can explain tradeoffs to an engineer and a VP in the same meeting.
• Ownership mindset. You’d rather fix it yourself than file a ticket.
• Bonus: experience with GLiNER, NER, or other information extraction models.
• Bonus: early stage startup experience.
• Willing to travel to customer sites as needed.