
Senior ML Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Check out my blog below for things I can talk about! (swarbrickjones.wordpress.com if thumbnail not showing).
University of Bristol
Doctor of Philosophy (PhD), Mathematics
January 1, 2009 – January 1, 2013
University of Oxford
MMATH, Mathematics
January 1, 2005 – January 1, 2009
Waymo
Senior ML Engineer
September 1, 2025 – Present
London · Hybrid
Tractable
Staff Applied Researcher
July 1, 2021 – Present
Tractable
Senior Applied Researcher
April 1, 2020 – July 1, 2021
Evolution AI
Machine Learning Researcher
July 1, 2017 – April 1, 2020
London, United Kingdom
Qubit.
Data Scientist
November 1, 2014 – July 1, 2017
London, United Kingdom
Ocado Technology
Data Scientist
June 1, 2013 – November 1, 2014
Cultural Fit Analysis
The candidate has a strong background in research and applied machine learning across diverse companies, from startups to larger tech firms. Their experience aligns well with roles requiring innovation and deep technical problem-solving. However, the target role is 'Data Analyst', which might be a step down from their 'Senior ML Engineer' and 'Staff Applied Researcher' roles, potentially indicating a mismatch in career trajectory or expectations. The breadth of skills is strong, but the direct alignment with a pure 'Data Analyst' role (which often focuses more on reporting, dashboards, and business intelligence rather than advanced ML model deployment) needs further clarification.
Soft Skills & Operational Fit
The candidate's extensive experience in research and development roles suggests strong analytical thinking, problem-solving, and innovation. Their work on deploying models implies an understanding of operationalizing data science solutions. However, specific soft skills like teamwork, communication, and leadership cannot be directly assessed from the provided data.