Remote-first AI/ML Engineer for Production Inference & RL

Boundless Network, Inc.; United States; On-site; USD 175,000 - 250,000; Full time

Benefits offered by this job

Equity

Health/dental/vision

Flexible PTO

Conference budget

Remote-friendly with off-sites

Job summary

Boundless Network, Inc. is seeking an Applied AI/ML Engineer to ship AI-powered products end-to-end on our growing GPU inference fleet.

You will own everything from serving low-latency inference to standing up reinforcement-learning post-training pipelines, turning ideas into production with a focus on throughput and cost on real GPUs. You will work autonomously in a fast-paced environment, collaborating with Infrastructure and Product.

Qualifications

• 3+ years shipping ML/AI systems to production.
• Hands-on experience serving LLM inference with vLLM, SGLang, or TensorRT-LLM.
• Experience with RL / post-training methods (GRPO, PPO, DPO, or SFT), or strong adjacent experience and a clear desire to go deep here.
• Strong Python and PyTorch.
• Working understanding of GPU execution: batching, memory, and basic CUDA concepts.
• Comfort operating in ambiguity with a strong bias for action.

Responsibilities

• End-to-End AI Product Delivery: Own AI features and products from prototype through production — model selection, serving, evaluation, and iteration.
• Inference Serving: Deploy and optimize LLM inference across the fleet using vLLM and SGLang. Tune batching, KV-cache, quantization, decoding, and multi-model routing to maximize throughput and minimize latency and cost per token.
• RL & Post-Training Harnesses: Build and operate reinforcement-learning and post-training pipelines using slime (Megatron-LM + SGLang) and Prime Intellect (prime-rl + Environments Hub/verifiers).
• Evaluation & Iteration: Build eval harnesses and benchmarks measuring quality, throughput, and cost to drive data-informed iteration.
• Work Across the Stack: Partner with Infrastructure on GPU scheduling and fleet utilization, and with Product on what to build next and why.

Skills

ML in prod

LLM inference

Reinforcement learning

Python

PyTorch

CUDA basics

Ambiguity tolerance

Tools

vLLM

SGLang

Megatron-LM

TensorRT-LLM

Job description

Boundless Network, Inc. is seeking an Applied AI/ML Engineer to ship AI-powered products end-to-end on our growing GPU inference fleet.

You will own everything from serving low-latency inference to standing up reinforcement-learning post-training pipelines, turning ideas into production with a focus on throughput and cost on real GPUs. You will work autonomously in a fast-paced environment, collaborating with Infrastructure and Product.