Snorkel AI · 1 month ago
Research Engineer – Training Infra
United States
Full-time
Remote
Senior Level
$180K/yr - $250K/yrSnorkel AI is on a mission to help enterprises transform expert knowledge into specialized AI at scale. As an Applied Research Engineer, you will own the infrastructure that powers model training and evaluation, building and operating GPU cluster infrastructure and ensuring that research and engineering teams can run experiments reliably and at scale.
Artificial Intelligence (AI)Big DataEnterprise SoftwareAI InfrastructureData Collection and LabelingMachine Learning
Responsibilities
Set up and manage GPU cluster infrastructure on major cloud providers (e.g., AWS HyperPod) for distributed model training, including networking, provisioning, and cost tracking
Build and operate job orchestration and scheduling systems (e.g., Kubernetes, Slurm, or cloud-native equivalents) to reliably launch and manage training, rollout, and evaluation jobs across multi-node clusters
Integrate and maintain ML training frameworks and post-training pipelines, ensuring they run stably and reproducibly at scale
Set up and maintain experiment tracking, dataset versioning, and model artifact management to support fast iteration
Monitor and optimize cluster health, inter-node communication, and resource utilization; implement fault tolerance and auto-recovery so long-running jobs survive node failures
Work closely with research scientists and ML engineers to understand requirements, unblock experiments, and evolve infrastructure as our training workloads needs change
Qualification
Required
Set up and manage GPU cluster infrastructure on major cloud providers (e.g., AWS HyperPod) for distributed model training, including networking, provisioning, and cost tracking
Build and operate job orchestration and scheduling systems (e.g., Kubernetes, Slurm, or cloud-native equivalents) to reliably launch and manage training, rollout, and evaluation jobs across multi-node clusters
Integrate and maintain ML training frameworks and post-training pipelines, ensuring they run stably and reproducibly at scale
Set up and maintain experiment tracking, dataset versioning, and model artifact management to support fast iteration
Monitor and optimize cluster health, inter-node communication, and resource utilization; implement fault tolerance and auto-recovery so long-running jobs survive node failures
Work closely with research scientists and ML engineers to understand requirements, unblock experiments, and evolve infrastructure as our training workloads needs change
Preferred
Hands-on experience managing GPU clusters on major cloud providers, including provisioning, network configuration, and cost management
Experience with distributed compute orchestration tools such as Kubernetes, Slurm, or equivalent cluster management systems
Working knowledge of distributed training concepts: parallelism strategies, memory optimization techniques, and inter-node communication
Experience with setting up, managing, and integrating ML experiment tracking and data/model versioning tools
Strong Python proficiency and solid software engineering fundamentals such as version control, modular design, and automation
Ability to work in a fast-moving, iterative environment and take end-to-end ownership of ambiguous infrastructure problems
Hands-on experience with post-training workflows such as supervised fine-tuning (SFT) or reinforcement learning (RLHF, GRPO, or similar) is a strong plus, but not required
Company
Snorkel AI
Snorkel AI is an AI platform that accelerates data labeling by using machine learning for faster model training.
Founded in 2019
51-200 employees
H1B Sponsorship
Snorkel AI 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
90%
Represents job field similar to this job
Engineering and Development
Management and Executive
Product Management
Sales
Trends of Total Sponsorships
*2026 (19)
2025 (15)
2024 (5)
2023 (4)
2022 (4)
2021 (10)
2020 (1)
Funding
Current Stage
Late StageTotal Funding
$235.25MKey Investors
Accenture VenturesAdditionQBE Ventures
2025-08-06Series Unknown
2025-05-29Series D· $100M
2024-01-23Series Unknown
Leadership Team
Alexander Ratner
Co-Founder and CEO
Henry Ehrenberg
Co-Founder
Recent News
startupresearcher.com
2026-06-03
Company data provided by crunchbase