Senior ML Science Manager
Leads and grows a team of ML scientists delivering user-facing machine learning products, while providing technical guidance and collaborating across ML, engineering, product, and design. Requires 5+ years of individual ML, AI, NLP, or data-related contributions and strong applied ML and coding skills.
About the job
Responsibilities
- Manage, mentor, and coach a team of 10+ ML scientists across offices in Dublin, London, and Berlin.
- Collaborate with ML, engineering, product, and design leaders to shape the team’s work and product impact.
- Enable the team to achieve high productivity, performance, and reliability.
- Expand the team and promote its brand internally and externally through recruitment and event planning.
Requirements
- Experience leading, developing, and supporting ML teams that deliver impact quickly.
- 5+ years of individual contributions in ML, AI, NLP, or a data-related field.
- Excellent applied machine learning and coding skills.
- Ability to thrive in ambiguous environments with a high degree of autonomy.
- Strong communication skills within technical teams and across disciplines.
- MSc or PhD in an ML-related field, or equivalent knowledge.
Nice-to-haves
- Experience shipping ML user-facing products.
- Experience in a research environment.
- Deep experience in an applicable ML area such as NLP, deep learning, Bayesian methods, reinforcement learning, or clustering.
- Data skills including visualization and SQL.
- Deep knowledge of software engineering practices.
- Experience recruiting ML scientists as a hiring manager.
Compensation and Benefits
- Competitive salary and equity.
- Lunch provided every weekday, snacks, and a fully stocked kitchen.
- Regular compensation reviews.
- Pension scheme with matching up to 4%.
- Life assurance and comprehensive health and dental insurance for employees and dependents.
- Flexible paid time off.
- Paid maternity leave and six weeks of paternity leave.
- Cycle-to-Work Scheme and secure bike storage.
- MacBooks are standard, with Windows available for certain roles.
- Hybrid working with at least three days per week in the office.
Skills
Machine Learning, Artificial Intelligence, Natural Language Processing, Deep Learning, Bayesian Methods, Reinforcement Learning, Clustering, SQL, Data Visualization, Software Engineering, Coding, Transformer Neural Networks, LLMs
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