Weights & Biases · 1 week ago
AI Engineer- ML/RL - Weights & Biases
San Francisco, CA
Full-time
Hybrid
Senior Level
$182K/yr - $242K/yr
5+ years expWeights & Biases, now part of CoreWeave, is focused on empowering developers with tools and infrastructure for AI. The AI Engineer role involves transforming cutting-edge research into practical workflows and collaborating with enterprises to enhance the application of AI technologies.
AI InfrastructureArtificial Intelligence (AI)Data VisualizationDeveloper ToolsGenerative AIMachine Learning
No H1B
U.S. Citizen Only
Responsibilities
Understand the state-of-the-art in deep learning / AI and turn the research into practical workflows that can be adopted by our users, the open source community & enterprise customers alike
Build in public: Publish engineering artifacts (code, reports, talks) that teach how to reproduce results; engage with OSS and customer engineers
Design and ship reference workflows for post-training & agents (SFT/DPO/GRPO/PPO, reward models, online RLHF/RLAIF) with reproducible repos, W&B Reports, and dashboards others can run
Own end-to-end demos: data → distributed training (FSDP/ZeRO/DeepSpeed/JAX pjit) → evaluation (lm-eval-harness + agent benches) → serving (vLLM/TensorRT-LLM/Triton/SGLang)
Partner with lighthouse customers; turn recurring patterns into templates and product feedback
Track recent advances (papers, releases, kernels), run focused ablations, and translate wins into production-ready workflows
Run growth experiments to track the usage of the Weights & Biases suite of products from the artifacts built
Qualification
Required
Deep learning: 5+ years training large models in PyTorch or JAX; strong numerics (autograd, initialization, mixed precision)
RL/RLHF: hands-on with SFT/DPO/GRPO/PPO, reward modeling, preference data pipelines, and online/offline RL for LLMs/agents
Inference/serving: production experience with vLLM/TensorRT-LLM/Triton; quantization, speculative decoding, caching
Evaluation: built task/agent harnesses with statistically sound metrics (variance, CIs, power) and failure taxonomies
Systems: strong Python plus one: CUDA/Triton kernels, custom C++ ops, or high-performance data ingestion
Reproducibility: rigorous experiment tracking (sweeps, artifacts, lineage); minimal repros others can run
Public signal: 2+ OSS repos/notebooks/talks with adoption (e.g., stars, forks, downloads, conference views)
Preferred
Paper-to-production within weeks at a top lab or applied-AI team (pretrain → post-train → eval → serve)
Data engines & feedback loops (rater pipelines, synthetic data, active learning)
Prior customer enablement with external adoption at scale
Benefits
Medical, dental, and vision insurance - 100% paid for by CoreWeave
Company-paid Life Insurance
Voluntary supplemental life insurance
Short and long-term disability insurance
Flexible Spending Account
Health Savings Account
Tuition Reimbursement
Ability to Participate in Employee Stock Purchase Program (ESPP)
Mental Wellness Benefits through Spring Health
Family-Forming support provided by Carrot
Paid Parental Leave
Flexible, full-service childcare support with Kinside
401(k) with a generous employer match
Flexible PTO
Catered lunch each day in our office and data center locations
A casual work environment
A work culture focused on innovative disruption
Company
Weights & Biases
Weights & Biases is a developer-first MLOps platform that builds machine learning performance visualization tools.
201-500 employees
Funding
Current Stage
Growth StageTotal Funding
$250MKey Investors
NVIDIAInsight PartnersCoatue
2025-03-04Acquired
2023-09-01Secondary Market
2023-08-09Series Unknown· $50M
Leadership Team
Chris Van Pelt
Co-Founder & CISO
Shawn Lewis
Founder/CTO
Recent News
Qualcomm Ventures
2026-01-20
Dynamic Business
2026-01-20
Company data provided by crunchbase