Fireworks
Applied Machine Learning Engineer
Salary not disclosedOnsite
- Engineering
- London
- Full time
- 5d ago
About the role
As an Applied Machine Learning Engineer, you will serve as the technical owner for customer engagements, embedding within client teams to deliver production-ready AI solutions. You will be responsible for scoping projects, optimizing model performance, and bridging the gap between customer requirements and the Fireworks platform. This role requires a deep technical background in software engineering, machine learning, and infrastructure to solve complex, real-world AI challenges.
Responsibilities
- Own customer deployments from initial scoping through to production as the primary technical lead.
- Embed directly within customer teams to understand their domain, data, and specific constraints.
- Execute fine-tuning and post-training workflows, including data preparation and model evaluation.
- Optimize model serving performance, cost, and deployment architecture on the Fireworks platform.
- Provide actionable product feedback to internal engineering teams based on customer needs.
Required skills
- Python
- Machine Learning
- Software Engineering
- GPU infrastructure
- Distributed serving
- Inference optimization
Nice to have
- SFT
- LoRA
- RLHF
- RLVR
- Quantization
- Speculative decoding
Qualifications
- PhD or MSc in a relevant field with experience post-training LLMs
- Experience with GPU infrastructure, distributed serving, or inference engines
- Founder or founding engineer experience
- Experience in a startup or fast-paced environment
About the Company
Fireworks is a platform for specialized intelligence that enables companies to build, train, and serve AI models tailored to their own data and workflows. Founded by the team behind PyTorch and backed by major venture capital firms, the company powers production AI across various modalities.