AI Engineer- ML​/RL

Job Description

Position: AI Engineer- ML/RL – Weights & Biases
What You’ll Do

The AI team is a hands‑on applied AI group at Weights & Biases that turns frontier research into teachable workflows. We collaborate with leading enterprises and the OSS community. We are the team that took W&B from a few hundred users to millions of users and one of the most beloved tools in the ML community.

This is a senior applied role at the research‑to‑production boundary. You will prototype, evaluate, and ship reusable DL/RL workflows for enterprise use on the W&B stack—then document and teach them to our customers and the community. The focus is application, not novel research: rapid prototyping, careful evaluation, and production‑grade reference implementations with clear trade‑offs.

About

The Role

• 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/Deep Speed/JAX pjit) → evaluation (lm‑eval‑harness + agent benches) → serving (vLLM/Tensor

RT‑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.

Who You Are

• 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/Tensor

RT‑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.

Wondering if you’re a good fit?

• You love turning cutting‑edge AI research into clean, benchmarked, production‑ready templates others can use today.

• You’re curious about RL‑based post‑training and agent evaluation, and maintain your own leaderboards.

• You’re an expert in at least one of: distributed training at scale, RLHF/GRPO systems, or low‑latency LLM serving—and you can demonstrate it with code and benchmarks.

What We Offer

The base pay and target total cash for this position range from $182,000 to $242,000. The starting salary will be determined based on job‑related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

• Medical, dental, and vision insurance – 100% paid for by Core Weave

• 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

•…