Applied Machine Learning Engineer (AI)

TL;DR

Applied Machine Learning Engineer (AI): Bridging the gap between cutting-edge AI research and practical customer applications with an accent on model fine-tuning, deployment, and performance optimization. Focus on building end-to-end AI-powered solutions, enabling new models, and collaborating with cross-functional teams to drive business value.

Location: Must be based in London, UK

Company

Fireworks AI is a high-growth, Series C startup building the future of generative AI infrastructure, backed by top-tier investors and founded by veterans of Meta PyTorch and Google Vertex AI.

What you will do

• Collaborate with GTM teams to ensure successful deployment of ML solutions for customers.
• Design, develop, and deploy end-to-end AI-powered applications.
• Build and present technical Proof of Concepts (PoCs) demonstrating AI capabilities.
• Contribute to the internal ML platform by adding features and resolving bugs.
• Enable and integrate new machine learning models into client environments.
• Optimize system performance, efficiency, and scalability of deployed models.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience in a software engineering role.
• Strong preference for experience in customer-facing roles.
• Robust coding skills, preferably with proficiency in Python.
• Proven ability to lead and execute complex technical projects.
• Strong interpersonal and communication skills for cross-functional collaboration.

Nice to have

• Master’s degree in Computer Science or Engineering.
• Experience working in a startup or fast-paced environment.
• Hands-on experience with SFT and RLHF/RFT.
• Solid understanding of generative AI, ML principles, and enterprise infrastructure.

Culture & Benefits

• Work on bleeding-edge AI infrastructure and low-latency inference challenges.
• High-impact role in a fast-growing, collaborative team environment.
• Opportunity to learn from world-class engineers and AI researchers.
• Direct ownership of projects with minimal bureaucracy.