Senior Software Engineer, Groq
Field-Programmable Gate Array
£81.8-107.3k
+ Equity
AI semiconductor chip manufacturer
Be an early applicant
AI semiconductor chip manufacturer
201-500 employees
Be an early applicant
£81.8-107.3k
+ Equity
201-500 employees
Company mission
To increase developer velocity in machine learning by leading the way with simple, fast, innovative solutions.
Role
Who you are
- You're deeply curious about system internals—from kernel-level interactions to hardware dependencies—and fearless enough to solve problems across abstraction layers down to the HDL for our chips
- You possess expertise in computer architecture, compiler backends, algorithms and hardware-software interfaces
- You've mastered system-level programming (Haskell, C++, or similar) with emphasis on low-level optimizations and hardware-aware design
- You consistently ship high-impact, production-ready code while collaborating effectively with cross-functional teams
- You excel at profiling and optimizing systems for latency, throughput, and efficiency, with zero tolerance for wasted cycles or resources
- You're committed to automated testing and CI/CD pipelines, believing that "untested code is broken code."
- You make pragmatic technical judgments, balancing short-term velocity with long-term system health
- You write empathetic, maintainable code with strong version control and modular design, prioritizing readability and usability for future teammates
- Nice to have: Experience with FPGA development
- Nice to have: Experience with VFIO drivers
- Nice to have: Familiarity with HDL languages
- Nice to have: Experience shipping complex projects in fast-paced environments while maintaining team alignment and stakeholder support
- Nice to have: Hands-on optimization of performance-critical applications using GPUs, FPGAs, or ASICs (e.g., memory management, kernel optimization)
- Nice to have: Familiarity with ML frameworks (e.g., PyTorch) and compiler tooling (e.g., MLIR) for AI/ML workflow integration
- Initiates (without derailing): Spots opportunities to solve problems or improve processes—while staying aligned with team priorities
- Builds stuff that actually ships: Values "code in prod" over "perfect slides." Delivers real value instead of polishing whiteboard ideas
- Is a craftsmanship junkie: Always asks, "How can we make this better?" and loves diving into details
- Plays to win (together): Believes winning means everyone wins. Aligns goals with teammates and customers because no one succeeds alone
- Owns it from whiteboard to watts: Takes full responsibility—debug it, deploy it, celebrate with users (or fix it again). Ensures code stays fast, scales well, and takes ownership of outcomes
What the job involves
- Deliver end to end FPGA solutions bridging the gap between the world and our accelerators
- Build and operate real-time, distributed compute frameworks and runtimes to deliver planet-scale inference for LLMs and advanced AI applications at ultra-low latency, optimized for heterogeneous hardware and dynamic global workloads
- Develop deterministic, low-overhead hardware abstractions for thousands of synchronously coordinated GroqChips across a software-scheduled interconnection network. Prioritize fault tolerance, real-time diagnostics, ultra-low-latency execution, and mission-critical reliability
- Future-proof Groq's software stack for next-gen silicon, innovative multi-chip topologies, emerging form factors, and heterogeneous co-processors (e.g., FPGAs)
- Foster collaboration across cloud, compiler, infra, data centers, and hardware teams to align engineering efforts, enable seamless integrations, and drive progress toward shared goals
- Your code will run at the edge of physics—every clock cycle saved reduces latency for millions of users and extends Groq's lead in the AI compute race
Salary benchmarks
Our take
Groq is an exciting semiconductor startup focused on creating advanced chips designed specifically for AI applications, particularly for AI inference, where models use trained data to deliver fast responses.
Groq aims to challenge Nvidia's dominance by focusing on speed and efficiency for AI deployment. While Nvidia's GPUs handle both training and running AI models, Groq's LPUs are optimized for inference tasks. With a recent $640M funding round, Groq plans to scale up and deploy over 100,000 LPUs by 2025.
To achieve this, the company has partnered with companies like Meta and Samsung, as well as sovereign entities like Saudi Aramco, showcasing the company's growth and potential. With its exciting technology, Groq is well-positioned to play a significant role in the AI chip market in the coming years.
Steph
Company Specialist at Welcome to the Jungle
Insights
-19% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Aug 2024
$640m
SERIES D
Jul 2024
$300m
SERIES D
Total funding: $1.3bn
Company HQ
Old Mountain View, Mountain View, CA
Leadership
Jonathan Ross
(Founder & CEO)Majored in Mathematics and Computer Science at NYU. Joined Google as a Software Engineer in 2011, and was promoted to Hardware Engineer in 2013. Co-founded Google's Tensor Processing Unit. Was also a Rapid Evaluator at Google X, and then founded Groq in 2016, acting as its CTO before becoming the CEO in 2018.
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