Senior ML Scientist - Hybrid, Product-Focused AI Leader

Fdetimes; Greater London; Hybrid; GBP 85,000 - 125,000; Full time

Job summary

Salesforce's Fin team is seeking a Machine Learning Specialist to identify opportunities and define models that improve customer experiences. The role emphasizes collaboration with product, design, and engineering to move prototypes into production across channels.

You will explore algorithms, run offline experiments, and help translate ML research into scalable features. Ideal candidates have 3–5 years of applied ML experience and strong statistical foundations.

Qualifications

• Broad applied machine learning knowledge.
• 3-5 years of applied ML experience.
• Practical statistics knowledge (experiment design, confounding).
• Intermediate programming skills (e.g., Python).
• Strong communication skills within engineering and across disciplines.
• Comfort with ambiguity and fast-paced product environment.
• Typically have advanced education in ML or related field (e.g. MSc).
• Scientific thinking and curiosity.

Responsibilities

• Identify ML opportunities that create value for customers.
• Define ML framing for product problems and plan experiments.
• Collaborate with Product and Design, and stakeholders.
• Conduct exploratory data analysis and research.
• Research and select algorithms and tools to prototype.
• Collaborate with engineering to move prototypes to production.
• Plan, measure, and share learnings to inform iteration.
• Partner with the team to build ML products.

Skills

Broad applied ML knowledge

Applied ML experience

Practical statistics knowledge

Programming skills

Communication skills

Ambiguity tolerance

Advanced ML education (e.g. MSc)

Scientific thinking

Education

Master’s in ML or related field

PhD in ML (bonus)

Tools

Python

SQL

Matplotlib

NLP

Job description

Salesforce's Fin team is seeking a Machine Learning Specialist to identify opportunities and define models that improve customer experiences. The role emphasizes collaboration with product, design, and engineering to move prototypes into production across channels.

You will explore algorithms, run offline experiments, and help translate ML research into scalable features. Ideal candidates have 3–5 years of applied ML experience and strong statistical foundations.