Staff Product Engineer, AI

We're looking for Staff Product Engineers to join the AI Group to build Fin's AI-powered products. Product Engineers working in ML work closely with both our ML Scientists and product teams. They must deeply understand our product, our customers, our ML tech stack and our broader product stack.

What you'll do

• Build the systems that power Fin's flagship AI products. This usually means working in our ML Python tech stack, but at times also means working across the product on our Rails app too.
• Work alongside our ML Scientists bring proof-of-concept code to production; ensuring it's robust and scalable for real-world use.
• Partner with product teams outside of our group, to shape the best AI-powered product experience for our customers.
• Contribute to all phases of software development including ideation, prototyping, and implementation and testing.
• Play an active role in the hiring, mentoring, and career development of other engineers.
• Raise the bar for technical standards, performance, reliability, and operational excellence within the group and across Fin.

What you'll need

• 10+ years of experience shipping high-quality products.
• No ML experience required. We believe you can be highly effective immediately by bringing excellent software engineering skills, and learn ML as you work on the team.
• You can demonstrate significant impact in the work that you have done.
• You take pride in having strong technical fundamentals; you love learning and are willing to work hard to invest in your development.
• Deep knowledge of a high-level programming language (for example, Ruby, Python, Javascript etc.) but it doesn't need to be a language that we use here.
• Strong willingness to fight for good outcomes.
• Bias towards progress over perfection.
• BSc in Computer Science, Maths or Statistics or related discipline.

Nice to have

• Previous experience in data analytics, or statistical role.

What they offer

• Competitive compensation determined by location, job level, skills, and experience.
• Incentive compensation, equity, and benefits eligibility.
• Health, wellbeing, family, and financial benefits programs.
• Hybrid working policy with flexibility to work from home.