Senior/Applied Scientist - AI Products

Carbon Data Solutions; United States; Ibrido; USD 140.000 - 210.000; Tempo pieno

Descrizione del lavoro

Xero is seeking an Applied Scientist or Senior Applied Scientist to turn ambiguous problems into data-driven products, moving from experimental design to prototyping, evaluation and production. You’ll work across heuristics, traditional ML, and LLMs, choosing the right approach for the problem at hand.

Based in Melbourne with a flexible hybrid model, you’ll collaborate with cross-functional peers, write testable Python code, build robust data pipelines, and advance scientific capability across

Competenze

• Scientific curiosity with solid software engineering fundamentals.
• Knowledge of probability, linear algebra and calculus for applying ML to product problems.
• Applied NLP or computer vision to live product challenges.
• Data wrangling and data pipelines experience.
• Ability to shape loosely defined problems into a clear research direction.

Mansioni

• Turn ambiguous problems into data-driven products and services across experimentation, prototyping and production.
• Choose the right approach for each problem (heuristic, ML model, or LLM) based on the context.
• Write testable, maintainable Python code and build robust data pipelines.

Conoscenze

Software engineering fundamentals

NLP

Computer vision

Probability/linear algebra/calculus

Python

Experimentation

Strumenti

Python

Descrizione del lavoro

The role and its impact

This role is open at Applied Scientist or Senior Applied Scientist level, and we'll assess your experience and demonstrated capability through the process to find the right fit.

You'll turn tough, ambiguous problems into elegant, data-driven products and services, moving between experimental design, prototyping, evaluation and more rigorous implementation depending on what the problem calls for. Some days that means a simple heuristic, others a traditional ML model, and others the latest in LLMs, and part of the job is judging which is genuinely right for the problem in front of you.

Working closely with cross-functional peers and holding coding standards high, your work will help ideas move smoothly from theory into real-world deployment. You'll also help lift scientific capability across Xero, contributing to a culture of intellectual rigour, healthy scepticism and mutual respect, Going Further by making evidence-based thinking part of how Xero builds.

The team and how they connect

You'll join AI Products, a close-knit team of seven based in Melbourne, building intelligent services that make a real difference for small businesses. The team balances business priorities with research demands to solve tangible customer problems, and works together to match each one to the right approach rather than reaching for complexity by default.

The team is currently working on

• Solving real business problems through experiment-based science, from framing the question through to rigorous implementation
• Choosing the right approach for each problem, whether that's a heuristic, a traditional ML model, or an LLM-based solution
• Writing testable, maintainable, reusable code in Python, building robust data pipelines alongside engineering peers
• Applying techniques such as NLP and computer vision to genuine product challenges at Xero's scale

Where and how you can work

Xero offers a flexible hybrid working model designed to blend the collaboration of office life with the autonomy of remote work. You will have access to our modern office spaces, with expectations around office days and collaborative 'boost days' aligned to help your team connect and ship great code effectively.

Here are some of the things we're looking for, for this role

• Scientific curiosity sits alongside solid software engineering fundamentals, so you can write code that's testable, maintainable and built to last.
• Probability, linear algebra and calculus aren't just theory to you, they're tools you reach for when applying machine learning to real product problems.
• You've genuinely applied techniques like NLP or computer vision to live product challenges, not just studied them.
• Data wrangling and pipeline work are familiar ground, and you know what good evaluation, measurement and experimentation look like in practice.
• Faced with a loosely defined business problem, you can shape it into a clear research direction, working closely with product, design and engineering partners along the way.
• You hold yourself to high standards of integrity and ownership, and you pair confidence in your work with a healthy dose of scepticism about it.