Member of Technical Staff New Grad
Fireworks AI
Member of Technical Staff New Grad
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.
This role is built for new graduates who want to work on real AI systems, in production, from the start. As a MTS at Fireworks, you'll write and ship code that runs on one of the busiest inference platforms in the world — serving hundreds of models to developers and enterprises at massive scale.
We hire new grads into teams across Engineering, and we match you to a team based on your strengths and interests after we get to know you. Depending on where you land, your work could span inference and performance, model training and fine-tuning, distributed systems and cloud infrastructure, developer platform and APIs, or product and full-stack application engineering. One application puts you in front of all of them.
You'll join with a senior engineer as your mentor and a structured ramp-up: you'll start on well-scoped, real problems alongside your mentor, then take ownership of features and systems of your own. We move fast, our bar is high, and we'll invest in getting you there.
We welcome candidates who have completed a Bachelor's or Master's degree within the last 6 months, or expect to complete one by Summer 2027. Note that candidates graduating in December 2026 are highly preferred and prioritized.
Ship production code: Design, build, and deploy features and services that customers depend on every day
Own problems end to end: Take a problem from ambiguous idea through design, implementation, testing, rollout, and operation
Make things faster and more reliable: Improve the performance, efficiency, and scalability of the systems you work on
Work with modern AI systems: Build with, on top of, or underneath large models — depending on your team, that could mean serving them, training them, evaluating them, or building products powered by them
Debug hard things: Dig into unfamiliar code and unfamiliar failures, and get to the root cause
Collaborate broadly: Work closely with engineers, researchers, product, and — on some teams — directly with customers
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, completed within the last 6 months or before the end of 2026
Strong programming fundamentals and solid grounding in data structures, algorithms, and systems
Practical software engineering experience through internships, research, open-source contributions, or substantial personal projects
Proficiency in at least one of Python, C++, Go, Rust, TypeScript, or a comparable language
Fluency with AI coding harnesses and a habit of using them well
Clear written and verbal communication, and the judgment to ask for help early
Comfort with ambiguity, fast iteration, and high ownership
We don't expect any single candidate to have all of these.
Hands-on experience building with LLMs or other ML models — coursework, projects, and internships all count
Experience with GPU programming, CUDA, kernel optimization, or performance profiling
Experience with distributed systems, Kubernetes, or cloud infrastructure (AWS/GCP/Azure)
Experience with PyTorch, model training, fine-tuning (SFT, RLHF/RFT), or inference serving
Experience shipping a full-stack or agentic application end to end, not just a notebook
Familiarity with evaluation, RAG systems, or observability for ML systems
Open-source contributions, competitive programming, or research publications
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