<div class="content-intro"><h2><strong>About Us:</strong></h2> <p data-start="107" data-end="729">At Fireworks, we’re building the future of generative AI infrastructure. Our platform delivers the highest-quality models with the fastest and most scalable inference in the industry. We’ve been independently benchmarked as the leader in LLM inference speed and are driving cutting-edge innovation through projects like our own function calling and multimodal models. Fireworks is a Series C company valued at $4 billion and backed by top investors including Benchmark, Sequoia, Lightspeed, Index, and Evantic. We’re an ambitious, collaborative team of builders, founded by veterans of Meta PyTorch and Google Vertex AI.</p></div><p>We are seeking a <strong>Member of Technical Staff, Evals & Post-Training Product</strong> to help define how developers improve models on Fireworks. This role sits at the intersection of product engineering, developer experience, and model quality.</p> <p>You will build the products and workflows that connect <strong>evaluation and post-training into a continuous loop</strong>: helping internal teams run evals at scale, enabling external developers through our open-source <strong>Eval Protocol SDK</strong>, and owning key product experiences for fine-tuning custom models on Fireworks.</p> <p>You will work across the stack—from APIs, SDKs, and backend systems to user-facing product surfaces in the web app—to make it easier for users to author evals, understand results, fine-tune models, and iterate quickly. You will also work directly with customers and internal teams to identify friction, support real-world use cases, and turn repeated pain points into reusable product capabilities.</p> <h2><strong>Key Responsibilities:</strong></h2> <ul> <li><strong>Build internal eval workflows:</strong> Design and scale evaluation tooling used by internal teams to measure model quality, compare model changes, and inform post-training decisions.</li> <li><strong>Own fine-tuning product experiences:</strong> Build and improve user-facing product workflows for post-training, including fine-tuning experiences across SFT, RFT, and related model-improvement capabilities.</li> <li><strong>Work closely with users:</strong> Partner with customers and internal stakeholders to understand evaluation and fine-tuning needs, support high-priority engagements, triage issues, and convert bespoke workflows into productized solutions.</li> </ul> <h2><strong>Minimum Requirements:</strong></h2> <ul> <li><strong>1 - 7 years of software engineering experience</strong> (We are hiring at multiple levels for this role).</li> <li><strong>Hands-on experience with LLM evaluations and/or post-training methods</strong>: How to design useful evals and use their results to guide model improvement.</li> <li><strong>Product Engineering Skills: </strong>The ability to work across backend systems and developer-facing product surfaces. Comfortable shipping full-stack features when needed.</li> <li><strong>Understanding of the GenAI Lifecycle:</strong> You understand the end-to-end workflow—from prompting a base model to curating a dataset, fine-tuning, and productionizing agents—and how these steps interconnect.</li> <li><strong>User-Centric Mindset:</strong> Willing to talk to users, triage GitHub issues for open-source projects, and build products from scratch to serve emerging needs.</li> </ul> <h2><strong>Preferred Qualifications:</strong></h2> <ul> <li><strong>3+ years of software engineering experience.</strong></li> <li><strong>Domain-Specific Evaluation Experience:</strong> Strong familiarity with designing and running evaluations for domain-specific use cases (e.g. medical, legal, coding, or custom internal datasets).</li> <li><strong>Open Source Contributions:</strong> Prior contributions to developer tools or AI/ML repositories.</li> <li><strong>Inference & Hardware Knowledge:</strong> Interest in the hardware side of AI—understanding GPU constraints, inference optimization techniques, and how they relate to model performance.</li> <li><strong>Startup DNA:</strong> Experience in fast-paced environments where you own features end-to-end.</li> </ul><div class="content-conclusion"><h2><strong>Why Fireworks AI?</strong></h2> <ul> <li>Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.</li> <li>Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.</li> <li>Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.</li> <li>Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.</li> </ul> <p><em>Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.</em></p></div>