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Manager, Machine Learning Engineer

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Description

Before we dive into the role, let’s talk about flexibility. At Zip, our office is in New York City but we can hire from anywhere across the United States. Our Zipsters can choose where and when they work by taking full advantage of our hybrid-work environment.

So whether you’re fully remote, mostly in the office or a mix of the two, you’ll be empowered to do whatever brings out your best.

About us

We are Zip, a global Buy Now, Pay Later company providing fair and seamless solutions that simplify how millions of people pay. Our journey began in Australia, has taken us to 14 countries (so far) - and we’re just getting started.

We exist to create a world where people can live fearlessly today, knowing they’re in control of tomorrow. Focused on product innovation that puts people at the centre, we put the financial well-being of our customers and merchant partners at the heart of everything that we do.

About the role

The vision of the Machine Learning (ML) Engineering team at Zip is to drive and enable ML usage across the company, and at all stages of our product’s life cycle. You’ll be in charge of making that vision a reality as we fundamentally believe machine learning engineering is the engine of our world-class data science and will lead us as a company. 

In this role, you will be the connective tissue between data engineering, data science, product, and software engineering. Supporting our Data Science teams in data sourcing, cleaning and access, FeatureStore, model development, and model observability. Build automation and productionisation, and provide ML Eng consultancy to all parties. You will work on cross-functional products and push the envelope on data and ML focused solutions.

What you'll do

  • Architecture: Own the vision for ML engineering in our company: the architecture of our platform and the technical approach to our solutions
  • Play the player-coach role: guide and mentor your squad while keeping your hands on the keyboard and shipping out brilliant outcomes yourself
  • Technically Deliver: Co-build our FeatureStore (utilized by multiple teams), serving capabilities, data quality, monitoring, cataloging, and the long list of additional capabilities
  • Focus on efficiencies: Hone our DS model lifecycle and push to beat current SLAs
  • Partner & Service: We’re stronger together, take the DS-ML partnership to new levels
  • Be a Leader: Lead by example, out of humility, and make sure we stay true to our family values. Care for your team with a servant leadership mindset
  • Be a Manager: Own project management, run a highly efficient team
  • Be an active member of the Data Leadership Team, have a daily say on our direction and continuously evolve your leadership skills, together with your fellow leaders

What you'll bring

  • You’re a culture ADD: You believe in and want to participate in a blameless culture that focuses on process and technology
  • You have worn the captain jersey before, leadership is not a new practice for you, it’s a skill you are in permanent pursuit to perfect
  • You have a proven track record in ML engineering; designing and implementing ML systems, working in cloud environments and their infrastructure, tackling big picture initiative and feeling comfortable charting a path forward where there’s ambiguity
  • Expertise with ML Ops, ML pipelines, algorithms, statistical methods, and analytics to solve real-world engineering problems
  • Comfortable operating at all levels of the predictive stack and user behavior modeling including data collection, feature engineering, batch training and low-latency online serving
  • Familiarity with Python development ecosystem and technologies like PySpark, Pandas, Jupyter notebooks
  • You obsess over the concept of reliable “ML Ops” platform and believe in our mission of building the underlying foundation for every decision we make as a company
  • You don’t sleep well at night when you leave work with a question unanswered. You feel accountable for everything you do, and it has been driving you your entire life
  • You’re a builder of teams, a driver of positive culture, you encourage collaboration and spending time together as a team. You take pride in bringing a team together, daily
  • You love learning new things: You know that there’s always more to learn, and it bothers you that there isn’t enough time in the day to learn about the next topic. You’re up-to-date on new trends in data – you know who’s using what to solve various problems and are excited for the next release of your favorite tool. If you can handle being thrown in the deep end of the pool, this team’s for you

Nice to have

  • Sense of humor is hugely preferred.
  • Past experience in the Financial industry
  • Experience with ML platforms/vendors like Dataiku/H2O/etc.
  • Experience with Feature Store design, development, and implementation
  • Devops experience / Data Science experience
  • Additional programming experience (Java/Scala/C#/etc.)
  • Strong mathematical skills with knowledge of statistical methods
  • An interesting life story / a cool hobby / a diverse background has proven to bring more to the table in terms of perspective, what's yours?
We’re proud to be a values-led business. They guide us in everything we do - how we work together and create game-changing experiences for our customers and fellow Zipsters.

If you only meet some of the requirements for this role, that's okay. We value a diverse range of backgrounds and ideas and believe this is fundamental for our future success. So, if you have the curiosity to learn and the willingness to teach what you know, we'd love to hear from you.

We pride ourselves on creating an inclusive workplace that provides equal opportunities to all persons regardless of their age, cultural background, sexual orientation, gender identity and expression, disability, veteran status, or anything else.

What’s in it for you?

We offer a variety of perks and benefits to support you at both work and home. Here’s a taste of what you can expect!

●     Flexible working culture
●     Share incentive programs
●     20 days PTO every year
●     Generous paid parental leave
●     Leading family support policies
●     100% employer covered insurance
●     Beautiful Midtown office with a casual dress code
●     Learning and wellness subscription stipend
●     Company-sponsored 401k match
●     Remote First Friendly!

We want to make sure our recruitment processes are accessible and inclusive for all people. If there's any adjustments that need to be made to ensure you have a fair and equal experience in our recruitment process please let your Talent Acquisition Partner know. We are also a proud 2022 Circle Back initiative employer and commit to respond to every applicant.

Join us on our mission to be the first payment choice, everywhere and every day.
  • New York, NY
  • Full-Time
  • Data & Analytics
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