Machine Learning Research Engineer Intern / Graduate

About Partly

Partly is a global AI infrastructure company revolutionizing the $2 trillion automotive repair industry. Founded by former Rocket Lab engineers, the company develops the frontier model Interpreter, the first AI designed specifically to interpret vehicle damage and identify necessary repair parts. Partly has rapidly expanded with offices in Austin (headquarters), London, Christchurch, and Auckland, supported by a $50 million Series B funding led by DST Global and other notable investors.

Role Overview

This hands-on role is ideal for early-career individuals eager to gain practical machine learning experience. As an intern or recent graduate ML research engineer, you will collaborate closely with the Applied Machine Learning team to develop and deploy machine-learning and algorithmic solutions addressing real-world vehicle and parts challenges. You will be mentored by seasoned engineers, focusing on turning noisy and complex data into impactful, measurable product outcomes.

Key Responsibilities

• Contribute to machine learning projects from problem framing to experimentation and production deployment under mentorship.
• Develop rigorous evaluation methods, including gold datasets and metrics, to accurately measure system performance in real-world scenarios.
• Apply and integrate various techniques such as modeling, ranking, classification, retrieval, and heuristic approaches, building sound judgment on their appropriate use.
• Design solutions with production constraints in mind, addressing latency, scalability, reliability, and failure modes.
• Collaborate cross-functionally with product and engineering teams to ensure alignment with business goals and operational efficiency.
• Maintain high standards for reproducible experiments, detailed documentation, and clear communication within a dynamic, fast-paced team environment.

Candidate Profile and Skills

• Currently studying or recently completed a degree in computer science, machine learning, mathematics, engineering, or a related technical field with strong fundamentals in algorithms and data structures.
• Practical experience through academic projects, personal initiatives, research, or internships involving machine learning or software development, with the ability to explain methodology and outcomes.
• Curiosity and a keen sense for evaluation metrics, favoring evidence of true improvements over superficial functionality.
• Engineering-oriented mindset with proficiency in writing maintainable code and eagerness to learn new technologies.
• Effective communication skills to articulate thought processes, seek guidance, and incorporate feedback in a collaborative low-bureaucracy environment.
• A proactive attitude toward learning, ownership of personal growth, and enthusiasm to tackle complex, real-world problems.
• Desirable: familiarity with technologies such as search, ranking, retrieval systems, graph algorithms, large language models (LLMs), or experience handling noisy and unstructured data.

Benefits and Culture

• Nutritious, catered lunches provided daily in offices including Christchurch.
• An annual wellness allowance equivalent to $1,500 for health or fitness-related expenses.
• Generous parental leave for primary caregivers, including three months fully paid leave and a flexible part-time transition back to work.
• Support for commuting with paid parking or allowance options.
• Workspaces designed for creativity and collaboration in architecturally designed offices close to cafes and social spots.
• An office-first approach in key cities to foster rapid decision-making and team bonding, alongside flexible scheduling to balance work and life.
• Regular social events and global company gatherings to celebrate achievements and strengthen team connections.

Additional Information

Partly is headquartered in Austin, Texas, with offices in London, Christchurch, and Auckland. The company facilitates onboarding at the nearest office and covers travel and accommodation for quarterly global team gatherings called "Season Openers." Relocation assistance is also available for candidates moving to join the team in New Zealand.