Lead Machine Learning Engineer / Staff Applied Scientist

ML Engineering @ Rokt

Rokt’s engineering team builds best-in-class ecommerce technology. Our bespoke platform handles millions of transactions per day and considers billions of data points, bringing Machine Learning Engineers the opportunity to research, design, build, train, and deploy models onto real-time systems running at internet scale.

Leading a field-topping team of Applied Scientists, you will undertake deep research and experimentation, harnessing a diversity of bleeding-edge ML theories, concepts, and models to improve sophisticated ML-driven systems powering 6.5 billion+ transactions per year. 

Who are we?

Rokt is a hyper-growth ecommerce leader. We enable companies to increase value by unlocking real-time relevancy in the moment that matters most, when customers are buying. Rokt’s AI & ML-powered ‘Brain’ and our ecommerce Rokt Network connect over 400 million customers into world leading companies.

We are a team of builders helping smart businesses find innovative ways to meet customer needs and create ancillary revenue streams. Leading companies drive 10-50% of additional revenue—and often all their profits—from the extra products or services they sell. This economic edge unleashes a world of possibilities for growth and innovation.

With a recent valuation of $3.5 billion USD, Rokt is highly profitable and growing quickly (40%+ revenue p/a over the past 10 years). 

Requirements

As a Lead Machine Learning Engineer / Senior Staff Applied Scientist, you bring deep expertise in machine learning and proven track record driving impact as a hands-on technical leader. You will lead a small, high-calibre team of Applied Scientists and collaborate with other engineering leaders and to tackle complex projects that increase the relevance of Rokt’s offerings to customers. 

You will be a seasoned expert who thrives when solving complex ML problems at scale - leading the cutting-edge ML research and production deployment of high-impact models which advance: recommender systems, conversion optimisation, user experience enhancement, and multi-task learning architectures. Ultimately, your models will help power over 6.5 billion+ targeted recommendations per year. 

Responsibilities:
Technical

• Own the research, design, development, testing, deployment and maintenance of machine learning systems and services at Rokt. 
• Conduct applied ML research, prototype new modeling approaches, and rigorously test innovations.
• Evaluate and improve model performance, ensuring robustness, scalability, and interpretability.
• Translate complex business needs into practical ML solutions, collaborating with product and engineering teams.
• Stay ahead of emerging ML trends, contributing to knowledge sharing through tech talks, brown bags, and best practice evangelism.

People Leadership

• Act as technical, project, and people leader to a small team of high-calibre MLEs
• Coach and develop a small team of mid-senior ML Engineers
• Provide leadership on complex technical issues, 
• Set standards for technical excellence - from coding to architectural best practices.
• Work cross-functionally to plan and manage delivery expectations of roadmap items.
• Work cross-functionally with engineering and product leadership to plan and manage delivery expectations of roadmap items.
• Actively monitor progress and intervene where required to mitigate risks and bottlenecks, managing expectations within and outside the team - e.g risks, unexpected issues
  

Requirements

• PhD or Master’s in Computer Science, Statistics, Mathematics, or related field with specialization in ML, AI, or Information Retrieval.
• 10+ years of industry experience building production-grade ML systems.
• Deep expertise in at least two:
• Reinforcement Learning (Bandits, Policy Optimization)
• Multi-Task Learning & Mixture of Experts (MMOE, PLE, DCN)
• Deep Learning Architectures (Transformers, Graph Neural Networks)
• Bayesian Methods & Probabilistic Modeling
• ML for Ads, E-commerce, or Two-Sided Marketplaces (big plus!)
• Proven ability to drive impact across multiple teams and organisation as a hand-on technical leader
• Bonus points if you are familiar with any of the following architectures or have experience with the models mentioned in this benchmark: DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, and GDCN.s

Benefits

We leverage best-in-class technology and market-leading innovation in AI and ML, with all of that being underlined by building and maintaining a fantastic and inclusive culture where people can be their authentic selves, and offering a great list of perks and benefits to go with it:

• Accelerate your career. We offer roadmaps to leadership and an annual $5000 training allowance
• Become a shareholder. Every Rokt’star gets equity in the company
• Enjoy catered lunch every day and healthy snacks in the office. Plus join the gym on us! 
• Extra leave (bonus annual leave, sabbatical leave etc.) 
• Work with the greatest talent in town
• See the world! We have offices in New York, Seattle, Sydney, Tokyo and London
  

We believe we’re better together. We love spending time together and are in the office most days (teams are in the office 4 days per week). We also get that you need to balance your life and your commitments so you have the flexibility to manage your own hours and can spend up to a week of every quarter working from anywhere.
About Rokt’stars:

As a mission-driven, hyper-growth community of curious explorers, our ambition is to unlock the full potential in ecommerce and beyond. Our bias for action means we are not afraid to quickly venture into uncharted territories, take risks or challenge the status quo; in doing so we either win or learn. We work together as one aligned team never letting egos get in the way of brilliant ideas. We value diversity, transparency and smart humble people who enjoy building a disruptive business together. We pride ourselves on being a force for good as we make the world better. 

If this sounds like a role you’d enjoy, apply here and you’ll hear from our recruiting team.