Applied Machine Learning Engineer

Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.

Responsibilities

• Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
• Build and present compelling Proofs of Concept (PoCs) that demonstrate the capabilities of our AI technology.
• Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
• Contribute to the internal ML platform, including adding features and resolving issues.
• Integrate and enable new machine learning models into the existing platform or client environments.
• Improve system performance, efficiency, and scalability of deployed models and applications.
• Work closely with partners to enable joint AI solutions and ensure seamless collaboration.

Requirements

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

Qualifications

• Master’s degree in Computer Science, Engineering, or a related technical field.
• Experience working in a startup or fast-paced environment.
• Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
• Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.

Benefits

• Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
• Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
• Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
• Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

Pay

Compensation Range: $170K - $240K