Applied Machine Learning Engineer
Fireworks AI
Applied Machine Learning Engineer
Fireworks AI
AI inference platform for model deployment
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.
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.
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.
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.
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.
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.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
AI inference platform for model deployment
Fireworks AI provides an AI inference platform that helps organizations run, customize, and deploy machine learning models. It supports deployment, fine-tuning, and inference workflows, with access to open-source models and on-demand deployment options through a subscription model. The platform enables users to configure and optimize models for production environments, manage variants, and scale AI workloads while controlling costs. Unlike some competitors, the emphasis is on end-to-end production-grade inference and fine-tuning across a range of clients, from tech firms to research institutions and enterprises, with tools tailored for rapid deployment and cost efficiency. The long-term goal is to expand the use of AI in production by building compound AI systems, growing the team, and delivering broader platform capabilities that accelerate AI adoption in real-world settings.
Explore more opportunities at Fireworks AI