Forward-Deployed ML Engineer, EMEA

Fireworks; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Job summary

Fireworks is seeking an Applied Machine Learning Engineer to own customer deployments end-to-end, embedding with client teams and delivering production-grade ML solutions. You will drive fine-tuning, performance optimization, and scalable inference while maintaining strong ties to product and engineering.

We value first principles thinking, ownership, and the ability to operate in a fast-paced startup environment, with a focus on building specialized intelligence for customers.

Qualifications

• Two or three spikes in two or all three areas.
• For the ML spike: formal training (PhD, PhD in progress, or a strong MSc) and experience post‑training LLMs specifically.
• For the infrastructure spike: experience with GPU infrastructure, distributed serving, or inference engines.
• Founder or founding engineer experience.
• Experience in a startup or fast‑paced environment.

Responsibilities

• Own Engagements: Take customer deployments from scoping through production, as the single accountable technical owner.
• Embed: Work directly inside customer teams; understand their domain, data, and constraints well enough to make decisions they trust.
• Train and Tune: Run fine‑tuning and post-training work where the engagement needs it, from data to evaluation to a model serving in production.
• Optimize: Drive serving performance and cost on Fireworks: model choice, deployment shape, and inference optimization.
• Scope Honestly: Assess what is achievable before we commit, and inherit what you scope.
• Product Signal: Feed what customers need back to product and engineering, with enough precision to be actionable.

Skills

Python

AI engineering

Open-source

Education

PhD in progress or MSc in relevant field

Tools

GPU infrastructure

Distributed serving

Inference engines

Job description

Fireworks is seeking an Applied Machine Learning Engineer to own customer deployments end-to-end, embedding with client teams and delivering production-grade ML solutions. You will drive fine-tuning, performance optimization, and scalable inference while maintaining strong ties to product and engineering.

We value first principles thinking, ownership, and the ability to operate in a fast-paced startup environment, with a focus on building specialized intelligence for customers.