Forward Deployed Engineer

fastino.ai; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Fastino is hiring a Forward Deployed Engineer in San Francisco to work inside customer stacks and deploy Fastino models in production. You will join a team building specialized language models and face hard technical problems while collaborating with customers and field engineers.

You will embed with customer teams, ship integrations and eval harnesses, and push for scalable, reusable tools and SDK improvements. Strong Python and cloud infra skills are essential for success.

Qualifications

• 3+ years as a software engineer, ideally with some customer-facing experience.
• Strong Python; comfortable with TypeScript, Go, or Rust.
• Hands-on experience shipping LLM/ML systems to production.
• Cloud and infra basics: AWS/GCP/Azure, Docker, Kubernetes, networking, and security.
• Clear communicator with an ownership mindset.
• Bonus: GLiNER/NER experience and early-stage startup exposure.
• Willing to travel to customer sites as needed.

Responsibilities

• Embed with customer engineering teams to scope, build, and deploy Fastino models.
• Write integrations, data pipelines, eval harnesses, and services on customer infra.
• Fine-tune and evaluate models on customer data and beat baselines on accuracy and latency.
• Debug auth, networking, GPU performance, data quality, and edge cases.
• Own the technical side of deals from first call through go-live with founders and AEs.
• Turn field work into reusable tools, reference architectures, and SDK improvements.
• Channel customer feedback to research and product teams.

Skills

Python

TypeScript

Go

Rust

LLM/ML production

Cloud

Docker

Kubernetes

Communication

Ownership mindset

Travel

GLiNER/NER

Education

BS or MS in Computer Science or related field

Tools

AWS

GCP

Azure

Job description

Forward Deployed Engineer

Full-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.