Applied AI/ML Engineer

Boundless Networks, Inc.; United States; Remote; USD 160,000 - 210,000; Full time

Benefits offered by this job

Competitive salary + equity

Health, dental, vision

Flexible PTO

Conference budget

Remote-first

Job summary

Boundless Networks, Inc. is seeking an experienced AI-focused engineer to own end-to-end AI product delivery, from prototype to production, including model selection, serving, evaluation, and iteration.

You will deploy and optimize LLM inference across the fleet, tune batching, KV-cache, quantization, and multi-model routing for performance, cost, and reliability. Remote-first, global team with equity and growth opportunities.

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 adjacent experience.
• Strong Python and PyTorch proficiency.
• Working understanding of GPU execution: batching, memory, CUDA basics.
• Comfort operating in ambiguity with a bias for action.

Responsibilities

• Own end-to-end AI product delivery from prototype to production.
• Deploy and optimize LLM inference across the fleet.
• Build and operate RL/post-training pipelines.
• Develop eval harnesses and benchmarks to drive iteration.
• Collaborate with Infra on GPU scheduling and fleet utilization.

Skills

3+ years shipping ML/AI systems toprod

LLM inference experience (vLLM, SGLang

RL & post-training methods

Python

PyTorch

GPU understanding (batching/memory/CUD

Tools

Kubernetes

Job description

What You'll Do

End-to-End AI Product Delivery: Own AI features and products from prototype through production — model selection, serving, evaluation, and iteration — shipping working software rather than research artifacts.

Inference Serving: Deploy and optimize LLM inference across the fleet using vLLM and SGLang. Tune continuous batching, KV-cache management, quantization, speculative 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 + the Environments Hub / verifiers). This includes reward and verifier design, rollout orchestration, weight synchronization, and keeping long-running training stable.

Evaluation & Iteration: Build eval harnesses and benchmarks that measure quality, throughput, and cost together, and use them to drive fast, 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.

• 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

Nice to Have

• Direct experience with slime, prime-rl, the verifiers library, or Megatron-LM
• Distributed training experience (FSDP, TP/PP/DP parallelism)
• Quantization (FP8/INT8), P/D disaggregation, or speculative decoding
• Experience with verifiable inference or large-scale distributed systems
• Kubernetes and container-based deployment
• Familiarity with GPU fleet orchestration (Ray, SkyPilot, Slurm)

Additional Requirements

• Candidates must include a public GitHub profile in their application.
• The GitHub profile should demonstrate a minimum of 1 year of activity/history.
• Applications that do not include a GitHub profile, or show insufficient activity, will not be considered.

At Boundless, we take care of our people, because building the future of AI compute starts with an empowered team. Here’s what you can expect when you join us:

• Competitive salary + equity allocation
• Health, dental, vision (for U.S. employees; region-adjusted globally)
• Flexible PTO
• Professional development and conference travel budget
• Remote-first with regular off-sites and a high-trust, high-velocity team environment

We are a global team, and applicants from around the world are welcome to apply.