ML Research Engineer Intern/Graduate, NZ

About Partly

Partly is building a global platform for replacement parts, beginning with auto parts, with the aim of making it easier for people everywhere to repair rather than replace. The company was founded by former Rocket Lab engineers and applies advanced technology to solve complex, high-impact problems in a massive $1.9 trillion industry. Its team has grown rapidly over the last year and continues to expand across Europe and Australasia. Partly works with major companies and fast-growing startups around the world, and its product is already embedded in hundreds of businesses that rely on it to catalogue and manage parts online.

The company is headquartered in Texas, with Product and Engineering based in Christchurch, New Zealand, and an early presence in London, UK. This position is specifically office-based at the Product and Engineering headquarters in Christchurch, NZ.

Role Overview

This opportunity is for an Intern Machine Learning Research Engineer joining the Applied ML team. You will help create and deliver machine-learning and algorithmic solutions for real problems in the vehicle and parts space. With support from experienced mentors, you will work through messy real-world inputs such as noisy data, edge cases, and changing constraints, turning them into measurable product outcomes.

The role is practical and hands-on, designed for someone at the beginning of their career who wants to grow through real shipping work. You will contribute to product-facing initiatives, including work on a foundational model for the vehicle and parts domain, and your impact will be measured by what gets built, validated, and released into production.

What You Will Be Doing

• Work on a defined Applied ML problem from problem framing through experimentation, and where appropriate, into production deployment, with guidance from your mentor.
• Help create evaluation frameworks that include gold datasets and metrics aligned with real-world performance.
• Develop practical judgment around modelling, ranking, classification, retrieval, and heuristic approaches, and learn when each method is most effective.
• Design with production constraints in mind, including latency, scale, failure handling, and reliability.
• Collaborate with product and engineering teammates to ensure your work translates into meaningful business and product outcomes.
• Maintain good engineering hygiene through reproducible experiments, structured notes, and thoughtful problem-solving.

What We Are Looking For

• Strong core fundamentals, with current or recent study in computer science, machine learning, mathematics, engineering, or a related discipline, plus solid knowledge of algorithms and data structures.
• Practical exposure to ML or software development through coursework, personal projects, research, or previous internships.
• Interest in evaluation and measurement, with a desire to understand whether an approach is genuinely better and how to assess that properly.
• An engineering-focused mindset, including writing clean enough code, adapting to new tools, and caring about making solutions work reliably.
• Good communication skills, including the ability to explain your thinking, ask for support when needed, and respond well to feedback in a collaborative environment.
• A strong learning orientation and willingness to take ownership, stretch yourself, and work on difficult real-world problems.
• Bonus exposure to search, ranking, retrieval, graph-based methods, large language models, or messy real-world datasets.
• If you do not meet every requirement but believe you can excel in the role, you are encouraged to apply.

Benefits

• A high-trust, low-process environment with very little bureaucracy.
• Competitive base pay plus equity for full-time employees.
• Flexible working hours, with no mandatory set schedule.
• An office-first setup in locations where the team has critical mass, including Christchurch.
• Two focus days each week with no meetings so you can do uninterrupted deep work.
• Generous leave flexibility, with trust given to take time off when needed.
• A well-equipped Christchurch CBD office with standing desks, healthy snacks, quality coffee, and drinks on tap.
• Regular learning opportunities such as Lunch n Learns and Fireside chats with notable leaders.
• Quarterly season openers and an annual global offsite for collaboration and planning.
• Monthly team lunches, celebrations, and social events.
• Parental leave support and flexible return-to-work arrangements.
• Payroll Giving support for donating to high-impact charities.

Additional Information

Partly values a culture of strong judgment, fast execution, and minimal unnecessary process. The team is expected to work hard while also being trusted to manage their own time responsibly. The company encourages applicants from underrepresented and marginalised groups, and invites candidates to apply even if they do not have every listed skill or experience.