ML Engineer

Octave X; Chicago (IL); Hybrid; USD 180,000 - 260,000; Full time

Job summary

A technology innovation company seeks an ML Engineer to design and implement AI systems tailored for enterprise needs. The role involves optimizing large-scale training pipelines and ensuring production reliability. Candidates should have 3+ years of experience, strong Python skills, and expertise in ML frameworks like PyTorch or JAX. This position offers a full-time schedule with a competitive salary range between $180,000 to $260,000 plus equity, accommodating both on-site and remote work options.

Qualifications

• 3+ years of machine learning engineering experience in production environments.
• Strong Python skills with deep experience in PyTorch and/or JAX.
• Hands-on experience with distributed training and model serving.
• Practical knowledge of transformer architectures and evaluation workflows.

Responsibilities

• Design and train formally verified AI systems for enterprise workloads.
• Build and optimize large-scale training and inference pipelines.
• Ship evaluation suites for safety, reliability, and model quality.
• Partner with product and infra teams to productionize new capabilities.
• Improve observability for model behavior and drift detection.

Skills

Machine learning engineering

Python

Distributed training

Model serving

Communication skills

Tools

PyTorch

JAX

Job description

You will work on model architecture, distributed training, inference optimization, and evaluation systems that power Tenzin and the broader Octave-X platform. The role bridges applied ML engineering and production reliability for regulated and high-trust environments.

Chicago, IL or Remote (US) Full-time $180,000 - $260,000 USD + equity

Role Snapshot

Team

Location

Chicago, IL or Remote (US)

Compensation

$180,000 - $260,000 USD + equity

About The Role

What You Will Build

Design and train formally verified AI systems for enterprise workloads.

• Build and optimize large-scale training and inference pipelines.
• Ship evaluation suites for safety, reliability, and model quality.
• Partner with product and infra teams to productionize new capabilities.
• Improve observability for model behavior and drift detection.
• Contribute to secure, testable, and maintainable ML infrastructure.

Required Qualifications

• 3+ years of machine learning engineering experience in production environments.
• Strong Python skills with deep experience in PyTorch and/or JAX.
• Hands-on experience with distributed training and model serving.
• Practical knowledge of transformer architectures and evaluation workflows.
• Strong communication skills and ownership mindset.

Nice To Have

• Formal methods, verification, or type-systems experience.
• Experience in regulated domains such as healthcare, finance, or public sector.
• Experience with GPU performance tuning and cost optimization.