Member of Technical Staff, Applied Machine Learning Engineer

The Role

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.

Key Responsibilities

• Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
• Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
• Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
• Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
• New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
• Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
• Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.

Minimum Qualifications

• 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.

Preferred 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.

Why Fireworks?

• 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.

Additional information

Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.