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Machine Learning Engineer

Xero is a beautiful, easy-to-use platform that helps small businesses and their accounting and bookkeeping advisors grow and thrive. 


At Xero, our purpose is to make life better for people in small business, their advisors, and communities around the world. This purpose sits at the centre of everything we do. We support our people to do the best work of their lives so that they can help small businesses succeed through better tools, information and connections. Because when they succeed they make a difference, and when millions of small businesses are making a difference, the world is a more beautiful place.


AI Products  at  Xero


The AI Products group exists to collaboratively build products that use AI and ML to reduce toil and deliver the right insight at the right time. Working within the Data & Science team, you will join a diverse, globally distributed team of scientists, engineers, product managers, and analysts who help Xero turn data into beautiful, insightful products.


The role 


ML engineers design and build the infrastructure and services that power AI products that serve millions of customers every day. They also work closely with Applied Scientists through the research and development process to create harnesses and to safely take models from research to production environments. As a Senior Machine Learning Engineer, you'll lead the technical delivery of projects and design system architectures, collaborating with senior colleagues.


Life at Xero


As a Machine Learning Engineer at Xero, you’ll be joining us on our mission of applying theory to real world problems in a pragmatic and creative way! You’ll have exposure to a variety of complex challenges at a global scale, whether it’s working with cutting edge language models or more traditional ML methods – you’ll get to create AI Products that delight our end users and help save them time!


To tackle the hard problems we’re aiming to solve, you’ll
  • Build our AI research and production infrastructure and services, ensuring their scalability while preserving flexibility for research teams
  • Make sure we're solving the right problems with the right methods
  • Share knowledge with colleagues and lifting the bar for the AI Products team
  • Work with teams across Xero to improve the quality and usability of data 


Here is what we look for in a Machine Learning Engineer at Xero :
  • Experience delivering ML and AI products at scale including strong SQL skills, understanding of distributed processing (data, ML, etc) and collaboration with scientific disciplines (statistics, ML) and Tensorflow is a nice to have
  • You like to solve hard problems and understanding how things work
  • You are comfortable learning new frameworks (distributed processing, ML, etc) and applying them to real problems
  • You are willing to dive into the unknown, and allow new information to change your decisions
  • Constant learning and growth are an important part of who you are
  • You are always willing to learn from others, ask for help and grow and mentor early career engineers


Why Xero? 

Offering very generous paid leave to use however you’d like (plus statutory holidays!), dedicated paid leave to care for your physical and mental wellbeing as well as an Employee Assistance Program to access mental health care for you and your family, health insurance, life insurance, and income protection, wellbeing and sports programmes, employee resource groups, 26 weeks of paid parental leave for primary caregivers, an Employee Share Plan, beautiful offices, flexible working, career development, and many other benefits that reflect our human value, you’ll do the best work of your life at Xero.

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$100000K
$140000K

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What You Should Know About Machine Learning Engineer, Xero

Xero is actively seeking a talented Machine Learning Engineer to join our innovative AI Products team. As part of our beautiful, user-centric platform, you'll play a critical role in helping small businesses and their advisors thrive. Our mission is to apply cutting-edge AI and machine learning techniques to deliver actionable insights that truly make a difference. At Xero, we prioritize our people, enabling them to create thoughtful and scalable solutions that enhance our services. In this role, you'll collaborate with a diverse team of data scientists, engineers, and product managers, designing and building the infrastructure for AI products that serve millions of customers worldwide. You'll face exciting challenges, such as building our research infrastructure and developing algorithms that ensure we solve the right problems with the right methods. If you're passionate about machine learning and eager to drive impactful projects at scale, we want you to help us create AI products that not only delight users but also save them valuable time. Plus, life at Xero means being part of a culture that values learning, collaboration, and personal growth, with plenty of perks like flexible working options and generous paid leave. Let’s make life better together!

Frequently Asked Questions (FAQs) for Machine Learning Engineer Role at Xero
What qualifications do I need to become a Machine Learning Engineer at Xero?

To succeed as a Machine Learning Engineer at Xero, candidates typically need experience in delivering machine learning and AI products at scale. Strong SQL skills and a good understanding of distributed processing are essential. Familiarity with TensorFlow is advantageous, as is collaboration with scientific disciplines such as statistics and machine learning.

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What is the work environment like for a Machine Learning Engineer at Xero?

As a Machine Learning Engineer at Xero, you'll enjoy a collaborative and supportive work environment filled with diverse professionals. Our flexible working arrangements allow you to thrive personally and professionally, while the company emphasizes continuous learning and growth within your role.

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What kind of projects will I work on as a Machine Learning Engineer at Xero?

In this role, you’ll tackle a variety of projects involving both cutting-edge language models and traditional machine learning methods. You will manage the infrastructure that supports our AI products, ensuring they are scalable and efficient while addressing real-world challenges faced by small businesses.

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What skills are necessary for a successful Machine Learning Engineer at Xero?

Successful Machine Learning Engineers at Xero embody strong problem-solving skills, a desire for continuous learning, and a solid grasp on distributed processing and machine learning principles. Being open to new frameworks and technologies is also crucial for adapting to the evolving landscape of AI.

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How does Xero support the personal development of its Machine Learning Engineers?

Xero fosters a culture of growth and development, offering comprehensive career progression pathways, mentoring opportunities, and encouraging participation in knowledge-sharing initiatives. This commitment empowers Machine Learning Engineers to elevate their skills and contribute effectively to the AI Products team.

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What benefits can I expect as a Machine Learning Engineer at Xero?

As a Machine Learning Engineer at Xero, you’ll enjoy numerous benefits, including generous paid leave, health insurance, life insurance, and mental wellness support programs. You’ll also have access to flexible work options, an Employee Assistance Program, and 26 weeks of paid parental leave for primary caregivers.

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Is teamwork important for a Machine Learning Engineer at Xero?

Yes, teamwork is one of the foundational pillars at Xero. Machine Learning Engineers work closely with data scientists, engineers, and product managers to share knowledge, drive projects, and collaboratively develop innovative solutions that align with our mission of making life better for small businesses.

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Common Interview Questions for Machine Learning Engineer
What is your experience with building scalable machine learning models?

When answering this question, discuss specific projects where you built and deployed machine learning models, emphasizing your approach to scalability, performance optimization, and any frameworks or tools you utilized to achieve your goals.

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Can you explain the difference between supervised and unsupervised learning?

This question aims to gauge your fundamental understanding of machine learning. Describe supervised learning as using labeled data to train models, while unsupervised learning involves discovering hidden patterns in unlabeled data, providing specific examples for clarity.

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How do you ensure your machine learning models remain effective over time?

Emphasize the importance of continuous monitoring and model retraining based on new data, along with techniques such as A/B testing and performance metrics to evaluate effectiveness, ensuring that your models adapt to changing conditions.

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Describe a challenging problem you faced in a previous project and how you solved it.

Share a specific example of a challenge related to machine learning, discussing the steps you took to address the issue, including any problem-solving techniques, collaboration with colleagues, and the outcome of your actions.

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How do you approach collaboration with data scientists and engineers?

In your answer, highlight the importance of clear communication and shared goals. Discuss how you foster a collaborative environment by regularly engaging with both teams, sharing insights, and integrating their feedback into your projects.

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What machine learning frameworks are you most comfortable using?

List the key frameworks you're experienced with, such as TensorFlow, scikit-learn, and PyTorch. Explain your familiarity with each framework, focusing on particular projects where you successfully applied them.

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How do you handle missing or unclean data in your datasets?

Discuss your data preprocessing techniques, such as imputation or removal of outliers, and emphasize the importance of understanding the impact of data quality on the performance of machine learning models.

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What strategies do you use to decide which algorithms to apply to a problem?

Describe your methodology in evaluating problem characteristics, such as data size, type, and the specific task at hand. Mention how you consider trade-offs between accuracy, interpretability, and computational efficiency when selecting algorithms.

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How do you stay current with the latest trends and advancements in machine learning?

Explain your commitment to ongoing education through resources like research papers, online courses, webinars, and participating in professional communities. Highlight how this knowledge informs your work and enhances your contributions.

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Why do you want to work as a Machine Learning Engineer at Xero?

Connect your passion for machine learning and AI with Xero's mission, demonstrating your alignment with their values of innovation and collaboration. Share specific interests in the projects they are working on and how you envision contributing to their success.

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Xero is a New Zealand–based technology company that offers a cloud-based accounting software for small businesses. They have offices in New Zealand, Australia, the United Kingdom, the United States, Canada, South Africa and Singapore.

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CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Customer-Centric
Social Impact Driven
Passion for Exploration
BENEFITS & PERKS
Family Medical Leave
Maternity Leave
Paternity Leave
Family Coverage (Insurance)
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
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Full-time, remote
DATE POSTED
November 29, 2024

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