Senior Machine Learning Engineer

Hybrid
Senior
💰$130–190K
🇦🇺 Australia
💰Equity
👶Paid parental leave
Machine Learning Developer
Data science & Analytics

⚡About Amber

Amber is a new way to buy and sell power, designed for a world powered by renewable energy. We are the "Only Wholesale Energy Retailer in Australia". We give customers direct access to the real-time wholesale electricity price as it varies every 30 mins and the technology to shift more of their energy usage to the times when cheaper renewables are available in the grid. It’s a cheaper way to buy power, a smarter way to sell power, and the fastest way for Australia to reach 100% renewable energy.

We are growing rapidly and have thousands of customers who love what we are doing and a great product that will play a significant role in driving Australia towards a renewable future. We are backed by Australia’s leading VCs (including Square Peg Capital and Main Sequence Ventures), impact-focused investors and individuals, and most recently by Commonwealth Bank, NRMA and Gentrack.

We’re now at a critical moment in taking the business to real scale as we disrupt a huge market for the better. You’d be a part of a rapidly growing team of over 120, with expertise across energy, technology, marketing, and operations. We’re committed to building a diverse and inclusive workplace and a great culture of people who love coming to work to build a better world.

💻 About the role

Want to help improve the environment by shifting Australia’s energy usage towards renewables?

We are currently hiring for a Senior Machine Learning Engineer. Amber provides a great opportunity to apply your skills as an Engineer to help enable the uptake of renewable energy. Our technology optimises thousands of batteries and other devices in our customers' homes, enabling them to time their usage to consume power at times of high renewable penetration (and cheap prices), and then export power back to the grid at critical times - letting them outbid coal and gas generators and earn potentially >$100 in an afternoon.

The Amber Electric product team develops and supports:

- Home automation integrations (to batteries, hot water systems and pool pumps, with EVs coming soon) that control electricity usage in response to pricing and renewable availability

- Mobile & Web apps for customers to monitor and manage their energy usage

- A pricing and billing engine for real time energy pricing

- The marketing site and associated tools to drive customer growth

The quality of our product is heavily dependant on the effectiveness of our optimisation algorithms and the forecasts they rely on. We use a mix of applied optimisation technologies, big data, and increasingly Machine Learning models to drive these optimisations and forecasts. Using customer feedback and data collected we shape future opportunities and scale to more devices to accelerate the renewable transition.

While we’re looking for talented and driven individuals our desire is to build a champion team, not a team of champions. We’re committed to building a diverse and inclusive workplace from the ground up. We want engineers who are as comfortable communicating with people as they are with their code.

Qualifications and Skills

  • 2+ years of experience as a Machine Learning Engineer, Data engineer, or similar role with data/ml operations exposure
  • Previous experience working on Mixed Integer Linear Programming problems utilising libraries such as Pyomo.
  • 5+ years of software engineering experience in any sub-discipline (we love generalists and career-changers). If you are someone who has been a software engineer previously and moved into data & ML, this would be a perfect role for you.
  • Strong programming skills in at least one language, ideally including Python
  • Fundamental modern software engineering skills (can design and implement a well-structured code base and software development cycle, including CI/CD, TDD, monitoring/logging)
  • An understanding of key machine learning and data science concepts with particular experience with models and techniques related to time series forecasting.
  • Previous experience with MLOps. You will be responsible for model development, model deployment, model versioning etc.
  • Data modelling and analysis skills with both DataFrame libraries such as Pandas or traditional SQL.
  • Happy/comfortable/willing to work in a start-up or fast paced environments

Key responsibilities

  • Selecting the best technology for a given data science or machine learning use case and leveraging existing tools or cloud services to assist.
  • Choosing and working with others on operational architecture for given big data / ML applications and ensuring their scalability.
  • Developing and deploying applied optimisation, big data, and machine learning solutions
  • Standing up cloud services to run ML workloads
  • Working with the broader engineering team and our customers to understand and enhance ML applications that help support the renewable transition and provide value in helping them manage their energy resources and requirements.
  • Working in a modern engineering and data stack. We use AWS, Snowflake and Dask, to name a few.

Benefits

  • We’re committed to building a diverse and inclusive workplace and a great culture of people who love coming to work to build a better world.
  • You’d be a part of a rapidly growing team of over 90 with expertise across energy, technology, marketing, and operations.
  • Be part of a growing technology start-up that will shape the future of household renewable energy use
  • Flexible working hours with provision for regular work from home arrangements and a central hub in Melbourne CBD
  • We offset 100% of your carbon footprint for as long as you work with us (via Nul)
  • Equitable gender-neutral parental leave policies
  • An external Employee Assistance Plan for mental health support
  • Competitive salary and shares in Amber
  • Annual Learning & Development budget to support your personal growth

$130,000 - $190,000 a year

Range is quoted excluding superannuation. All roles at Amber include employee stock options.

This is a full-time role to be based ideally from Melbourne, but we are also open to considering the right candidate anywhere within Australia.

We are also open to working 4 days a week, if that's what you are looking for. We do have an office in the Melbourne CBD, where we work flexibly between the office and home. For those based in Sydney, catch up in a co-working space every now and then, and rest of the locations in Australia work from home. We expect to remain Melbourne based but maintain flexibility between the office and WFH.

🌈 If this kind of work gets you excited, we'd love to hear from you!

Even if you don’t meet 100% of the requirements listed above, we still encourage you to apply. We're open to all backgrounds and encourage people from underrepresented groups to apply. We never discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, or disability status.

✍️ How to Apply

Please include your resume and a cover letter and tell us one specific way you could use your technical skills to improve a household's energy use under the Amber model.

Our process will generally be as follows:

- A screening interview with our talent team

- A take-home technical challenge that should take no longer than four hours

- A technical interview with one of the members of our engineering team

- A manager interview with two of our Engineering leaders

We promise to be respectful of your time as an applicant while trying to be as thorough as possible in finding the right fit for our team.

Applications only from candidates already based in Australia please. No recruitment firms.

 

Amber Electric

Amber Electric

A renewable energy start-up committed to building a diverse and inclusive workplace and a great culture, with a rapidly growing team of over 70 experts across energy, technology, marketing, and operations

🌞Clean energy
Renewable Energy
Startups
Technology
Marketing

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🏭services for renewable energy
🎂2017

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