Machine Learning Engineer

Doghouse Recruitment; United States; Remote; USD 160,000 - 230,000; Full time

Job summary

A recruitment agency is seeking a Senior HFT & Trading Tech Recruiter specializing in AI/ML solutions. This remote role targets engineers in distributed training and GPU infrastructure. Candidates should have a strong ML background with experience in PyTorch or JAX. Offering a competitive salary up to $230k base, plus a bonus depending on seniority.

Qualifications

• 7+ years in ML infrastructure, MLOps, or similar roles.
• Deep experience with PyTorch or JAX and multi-node training.
• Strong understanding of ML pipeline design, performance tuning, and deployment.

Responsibilities

• Design and deploy high-performance ML pipelines across hundreds/thousands of GPUs.
• Guide customers in optimizing distributed training and inference setups.
• Deliver tech talks, contribute to whitepapers, and gather feedback for product teams.
• Work cross-functionally with engineering, product, and R&D to shape our AI platform.

Skills

ML infrastructure

MLOps

PyTorch

JAX

Python

Job description

This range is provided by Doghouse Recruitment. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$160,000.00/yr - $230,000.00/yr

Direct message the job poster from Doghouse Recruitment

Senior HFT & Trading Tech Recruiter | C++ · Rust · Core Linux · Low Latency · Network Engineering

AI/ML Solutions Architect – Distributed Training & GPU Infrastructure

Location: Remote from anywhere in the U.S.

Salary: Up to $230k base + bonus, depending on seniority

Join a fast-moving AI infrastructure team working on the cutting edge of large-scale ML workloads. This role is ideal for engineers who enjoy solving deep technical challenges in distributed training, multi-GPU systems, and scalable AI inference infrastructure. You'll work directly with AI-focused clients, helping them get the most out of modern GPUs (H100, B200, etc.) and ML frameworks like PyTorch and JAX.

Responsibilities

• Work alongside world-class engineers building the infrastructure behind next-gen AI systems. As part of the customer solutions team, you'll:
• Design and deploy high-performance ML pipelines across hundreds/thousands of GPUs
• Guide customers in optimizing distributed training and inference setups
• Deliver tech talks, contribute to whitepapers, and gather feedback for product teams
• Work cross-functionally with engineering, product, and R&D to shape our AI platform

Required Skills

• 7+ years in ML infrastructure, MLOps, or similar roles
• Deep experience with PyTorch or JAX and multi-node training
• Strong understanding of ML pipeline design, performance tuning, and deployment
• Programming in Python (Go, Java, or C++ a plus)

Bonus

Experience moving ML systems from POC to production-scale; familiarity with Hugging Face, TensorFlow, or inference optimization

We’re looking for hands-on engineers who understand real-world ML problems and love building scalable, robust systems. If you thrive at the intersection of infrastructure and AI, this is your next move.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• IT Services and IT Consulting, Technology, Information and Media, and IT System Design Services

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