Senior ML Science Manager

What's the opportunity?

Fin's AI Group is responsible for defining new ML products, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers’ hands.

We are extremely product-focussed. Our team of 50+ ML scientists, ML engineers, designers and researchers works in partnership with other teams across the whole company. We move to production fast, often shipping to beta in weeks after a successful offline test.

We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, novel applications of transformer neural networks and fine-tuned LLMs. We test and measure the real customer impact of everything we deploy.

We plan to double in size, and are on the lookout for an experienced manager to manage a team of highly-performing ML scientists. Engineering managers in Fin are not just people managers: they also have a track record of IC contributions, and can stay close to the work of their team. We won’t ask you to write code every day, but you should feel comfortable giving technical advice to your team and having a good deep grasp of what it should (or shouldn’t!) work on (and maybe even do an occasional code review or a PR).

What will I be doing?

• Managing, mentoring and coaching a team of 10+ ML scientists, spread across our three offices in Dublin, London and Berlin.
• Collaborating with ML, engineering, product, and design leaders to shape work of the team and the impact it has on our products.
• Enabling your team to achieve high levels of productivity, performance and reliability.
• Expanding the team and promoting its brand both internally and externally (recruitment, event planning, etc.).

What skills might I need?

• Experience leading, developing and supporting ML teams that deliver impact quickly.
• A 5+ year track record of your own individual contributions in ML, AI, NLP, or data-related field.
• Excellent applied ML and coding skills.
• The ability to thrive in an ambiguous environment with a high degree of autonomy.
• Strong communication skills, both within technical teams and across disciplines.
• MSc or PhD in an ML-related field, or similar knowledge.

Bonus skills & attributes

• Track record shipping ML user-facing products.
• Experience in a research environment.
• Deep experience in an applicable ML area - e.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering.
• Data skills: visualization, SQL etc.
• Deep knowledge of software engineering practices.
• Experience in recruiting ML scientists in a capacity similar to a hiring manager.