Junior Machine Learning Engineer

What We’re Looking For
We’re looking for a junior machine learning engineer to join our team and grow into a strong, hands‑on ML engineer.

This is a role for someone early in their career who is eager to learn, comfortable getting their hands dirty with real data, and motivated to build a solid foundation in applied machine learning.

You will work under the direction of senior ML and engineering staff, contributing to real models and pipelines while developing your skills and judgment over time.

Position Overview
Working closely with senior engineers, you will:

implement, train, and evaluate models under guidance

prepare and explore real-world data

help build and maintain data pipelines

support experiments and document results

This role is hands‑on and engineering‑focused.

You will be writing code, working with messy, real‑world data, and learning how machine learning systems are built and run in practice.

Over time, as you build experience, you will take on more ownership and tackle increasingly open‑ended problems.

Duties and Responsibilities

Implement and train models under the guidance of senior engineers

Prepare, clean, and explore datasets, including feature engineering

Run experiments, record results, and help interpret findings

Build and maintain parts of the data pipeline and supporting tooling

Help integrate models into larger systems alongside the team

Write clear, testable, and maintainable code

Ask good questions, seek feedback, and learn from code review

Required Skills / Experience

0–2 years of experience in machine learning, or strong academic or project experience

Programming ability in Python

Solid grounding in machine learning fundamentals

Willingness to work with real-world, imperfect data

Strong problem‑solving ability and a desire to learn

Ability to take direction and incorporate feedback

Clear communication in a team environment

What this Role Requires

Eagerness to learn and grow quickly

Comfort working with guidance and asking for help when needed

Pragmatism and a willingness to see tasks through

Attention to detail and care in the work

Ownership of your own learning and contributions

Nice to haves

Coursework, internships, or projects involving anomaly detection, time‑series, or behavioral modeling

Exposure to streaming or telemetry data

Familiarity with common ML libraries and tooling

Experience contributing to a shared codebase

Benefits

Dental care

Extended health care

On‑site parking

Paid time off

Vision care

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