Member of Technical Staff (New Grad (Bachelor of Science/Master of Science))
Posted Updated
Description
- 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
- Practical software engineering experience through internships, research, open-source contributions, or substantial personal projects
- 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
- Proficiency in at least one of Python, C++, Go, Rust, TypeScript, or a comparable language
- 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
- Comfort with ambiguity, fast iteration, and high ownership
- 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 shipping a full-stack or agentic application end to end, not just a notebook
- Experience with PyTorch, model training, fine-tuning (SFT, RLHF/RFT), or inference serving
- Familiarity with evaluation, RAG systems, or observability for ML systems
- Open-source contributions, competitive programming, or research publications