Staff Machine Learning Scientist
Salary not listed • London, England • Full-time
Posted 1y ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
Job Location
London, England
Also open in Dublin, Ireland
Tech Stack
Remote Work Policy
On-site
Employment Type
Full-time
Categories
Machine Learning Engineer
About the job
Fin, now part of Salesforce, is seeking a Staff Machine Learning Scientist to join their Machine Learning team. This team is responsible for defining new ML features, researching algorithms and technologies, and rapidly prototyping solutions for customers. They work closely with Product and Design teams, with dedicated ML product engineers enabling fast production deployment, often shipping to beta within weeks of successful offline testing. The team has a history of productizing a wide range of ML applications, from classic supervised models to advanced unsupervised clustering and transformer neural networks, always measuring real customer impact.
Responsibilities
- Play an active role in hiring, mentoring, and career development of other engineers.
- Raise technical standards, performance, reliability, and operational excellence.
- Identify areas where ML can create customer value.
- Define the ML approach for product problems in collaboration with stakeholders.
- Conduct exploratory data analysis and research to understand problem areas.
- Research and select appropriate algorithms and tools, balancing pragmatism with innovation.
- Perform offline evaluations to validate algorithm effectiveness.
- Collaborate with engineers to bring prototypes to production.
- Plan, measure, and socialize learnings to inform product iteration.
- Partner with the team and other departments to build excellent ML products.
Requirements
- 5-8 years of applied ML experience.
- Previous experience in a senior/staff role (data science, software development, or academic).
- Demonstrated significant impact of work on products or teams.
- Strong programming skills.
- Experience as the primary technical leader for a team.
- Strong communication skills, both within engineering and across disciplines.
- Comfort with ambiguity.
- Advanced education in ML or a related field (e.g., MSc).
- Scientific thinking skills.
Benefits
- Support for health and wellbeing.
- Support for family.
- Support for time away from work.
- Support for financial future.
- Flexibility to work from home.
- Opportunities for career development.