# AI Researcher, Core ML (Turbo)

**Company:** [Together AI](https://hotfix.jobs/companies/together-ai)
**Location:** San Francisco, CA
**Role:** AI Research
**Salary:** $200k – $280k/yr
**Experience:** 3+ years
**Skills:** Python, Sglang, vLLM, TensorRT, Fastertransformer, RLHF, Dpo, Grpo, Gpu Optimization, Speculative Decoding
**Posted:** 2026-02-14

> Develops efficient inference engines and RL/post-training pipelines for production-scale LLMs, optimizing algorithms, systems, and performance across the stack. Requires 3+ years in ML systems/RL/inference and advanced degree.

## Job Description

## Requirements

- Strong expertise in at least one area, with interest to grow across: large-scale inference systems (SGLang, vLLM, FasterTransformer, TensorRT), GPU performance, distributed serving; RL/post-training for LLMs (GRPO, RLHF/RLAIF, DPO); Transformer architectures; distributed systems/HPC for ML.
- Comfortable from algorithms to engines: strong **Python** coding, profiling/optimizing GPU/networking/memory, implementing production-grade features.
- Solid research foundation: track record in ML systems/RL/large-scale training (papers, open-source, production); ability to read papers and implement changes.
- Full-stack problem-solving: identify bottlenecks, collaborate across teams.

**Minimum qualifications:**
- 3+ years in ML systems, large-scale model training/inference, or equivalent.
- Advanced degree in CS, EE, or related field, or equivalent experience.
- Experience owning complex technical projects end-to-end.

## Responsibilities

- **Advance inference efficiency:** Design/prototype algorithms/architectures/scheduling; implement in engines (SGLang/vLLM, ATLAS, quantization); profile/optimize GPU/networking/memory.
- **Unify inference with RL/post-training:** Design/operate RL pipelines (RLHF, RLAIF, GRPO, DPO); optimize with inference-aware techniques (async rollouts, speculative decoding); train/evaluate frontier models; co-design algorithms/infra; run ablations.
- **Own production systems:** Profile/debug/optimize services; drive engine modifications (kernels, scheduling, APIs); establish metrics/benchmarks.
- **Technical leadership (Staff level):** Set direction for cross-team efforts; mentor engineers/researchers.

## Compensation

US base salary: **$200,000 - $280,000** + equity + benefits.

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