Cohere · 10 hours ago
Staff Software Engineer, GPU Infrastructure (HPC)
San Francisco, CA
Full-time
Hybrid
Lead/StaffCohere is a company dedicated to scaling intelligence to serve humanity by training and deploying AI models. The Staff Software Engineer will be responsible for building and managing ML-optimized HPC infrastructure, collaborating closely with AI researchers to support their workload needs and ensure high performance and reliability.
Artificial Intelligence (AI)Generative AIMachine LearningNatural Language Processing
Responsibilities
Build and scale ML-optimized HPC infrastructure: Deploy and manage Kubernetes-based GPU/TPU superclusters across multiple clouds, ensuring high throughput and low-latency performance for AI workloads
Optimize for AI/ML training: Collaborate with cloud providers to fine-tune infrastructure for cost efficiency, reliability, and performance, leveraging technologies like RDMA, NCCL, and high-speed interconnects
Troubleshoot and resolve complex issues: Proactively identify and resolve infrastructure bottlenecks, performance degradation, and system failures to ensure minimal disruption to AI/ML workflows
Enable researchers with self-service tools: Design intuitive interfaces and workflows that allow researchers to monitor, debug, and optimize their training jobs independently
Drive innovation in ML infrastructure: Work closely with AI researchers to understand emerging needs (e.g., JAX, PyTorch, distributed training) and translate them into robust, scalable infrastructure solutions
Champion best practices: Advocate for observability, automation, and infrastructure-as-code (IaC) across the organization, ensuring systems are maintainable and resilient
Mentorship and collaboration: Share expertise through code reviews, documentation, and cross-team collaboration, fostering a culture of knowledge transfer and engineering excellence
Qualification
Required
Deep expertise in ML/HPC infrastructure: Experience with GPU/TPU clusters, distributed training frameworks (JAX, PyTorch, TensorFlow), and high-performance computing (HPC) environments
Kubernetes at scale: Proven ability to deploy, manage, and troubleshoot cloud-native Kubernetes clusters for AI workloads
Strong programming skills: Proficiency in Python (for ML tooling) and Go (for systems engineering), with a preference for open-source contributions over reinventing solutions
Low-level systems knowledge: Familiarity with Linux internals, RDMA networking, and performance optimization for ML workloads
Research collaboration experience: A track record of working closely with AI researchers or ML engineers to solve infrastructure challenges
Self-directed problem-solving: The ability to identify bottlenecks, propose solutions, and drive impact in a fast-paced environment
Benefits
An open and inclusive culture and work environment
Work closely with a team on the cutting edge of AI research
Weekly lunch stipend, in-office lunches & snacks
Full health and dental benefits, including a separate budget to take care of your mental health
100% Parental Leave top-up for up to 6 months
Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement
Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend
6 weeks of vacation (30 working days!)
Company
Cohere
Cohere is an enterprise AI firm developing secure and private AI technology to address real-world business challenges.
Founded in 2019
201-500 employees
H1B Sponsorship
Cohere has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (9)
2024 (14)
2023 (13)
2022 (5)
2021 (2)
Funding
Current Stage
Late StageTotal Funding
$1.71BKey Investors
Government of CanadaTiger Global ManagementIndex Ventures
2025-09-24Series D· $100M
2025-08-14Series D· $500M
2025-06-17Secondary Market
Leadership Team
Aidan Gomez
cofounder + ceo
Ivan Zhang
Co-Founder
Recent News
2025-12-27
2025-12-24
2025-12-20
Company data provided by crunchbase