Data Scientist developing advanced data science models to enhance electric transmission and distribution grid reliability at PG&E. Collaborating with cross - functional teams to lead data science initiatives.
About the role
- Senior Machine Learning Engineer building and integrating advanced ML capabilities for engineering decisions at Secondmind. Collaborating with customers and research teams to enhance product functionality.
Responsibilities
- Developing and integrating ML capabilities : Building the ML capabilities that power the product.
- Customer guidance : Helping customers frame their engineering problems in terms our product can address, and guiding them through new ways of working.
- Diagnosing complex issues : When a customer's data goes into the product and something isn't right, you are the person who can unpick whether it's a data quality issue, unexpected model behaviour, a configuration problem, or a genuine bug.
- Shaping product direction : You sit at the intersection of what our researchers envision, what our customers actually need, and what is realistic to build and maintain in production.
- Codebase stewardship : Contributing to and maintaining a production codebase that interfaces with real test benches and simulation toolchains.
Requirements
- Strong theoretical and practical foundations in machine learning.
- Proficiency in Python and comfort working in a large, production-grade codebase (not just notebooks and scripts).
- Hands-on experience with at least one major ML framework (e.g. TensorFlow, PyTorch).
- The ability to thrive in complexity and ambiguity.
- Excellent judgement about when to work independently and when to ask for help, with the interpersonal skills to draw out the knowledge of domain experts, researchers, and engineers around you.
- Familiarity with automotive, manufacturing, or other engineering sectors.
- Experience working directly with customers or external stakeholders in a technical capacity.
- Strong foundations in probabilistic modelling (Gaussian processes, Bayesian methods, uncertainty quantification) and practical experience applying these techniques to real problems.
- Experience with active learning, Bayesian optimisation, or design of experiments.
- Familiarity with TensorFlow.
Benefits
- Competitive salary - reviewed annually
- 25 days annual leave, plus statutory bank holidays
- TGIF: The last Friday of every month is a half day for our employees
- Enhanced family leave policies
- Salary Sacrifice Pension Scheme
- Life Assurance of 4x salary
- Private Medical Insurance
- Eyecare Policy
- Dental Cash Plan
- Stock Options (where applicable)
- Free 24 hour access on-site gym
- Discount Shopping & Wellbeing Platform
- Employee Assistance Programme
- Values Award Scheme
- Cambridge Botanic Garden membership
- Social events, game nights and sports groups
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
No Education Requirement
Tech skills
Location requirements
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