Job Details

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Overview

We're partnered with a stealth, high-growth startup that's building next-generation machine learning systems to power real-world decision-making at scale. The team is hiring one of its first Machine Learning Engineers to help design, train, and deploy production models that sit at the core of the company's technology stack. This is a rare opportunity to join an elite founding team early—working directly with experienced engineers and researchers to shape both the technical direction and product architecture from the ground up.

Responsibilities

• Design, build, and maintain machine learning models that power core product features.
• Develop scalable data pipelines, training workflows, and deployment infrastructure.
• Collaborate closely with product and engineering teams to bring ML systems into production.
• Continuously monitor, evaluate, and improve model performance and reliability.
• Explore and implement novel model architectures to solve complex technical challenges.

Qualifications

• Bachelor's or Master's in Computer Science, Engineering, Math, or a related field from a top-tier university (GPA 3.7+ preferred).
• 2–5 years of experience in machine learning or software engineering roles.
• Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong understanding of algorithms, data structures, and systems design.
• Experience deploying and maintaining production ML systems.
• Comfortable in a fast-paced, high-autonomy startup environment.

What You'll Get

• Early ownership and impact in a technically ambitious company.
• Opportunity to build and scale ML infrastructure from day one.
• Direct collaboration with a world-class founding team.
• Access to significant data resources and modern tooling.
• Competitive compensation with meaningful equity upside.
• A culture that prioritizes technical rigor, creativity, and rapid iteration.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Industries

• Software Development and Data Infrastructure and Analytics

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