Machine Learning Specialist (Finance)
Job details
Safe Intelligence is on a mission to make AI safe and reliable for anyone to use. To help us succeed, our team is looking for Machine Learning Specialists, and we’re hoping it’s you! In this role, you’ll play a leading role in helping both customers and driving our product forward by helping our internal team apply advanced validation techniques to their machine-learning models. This role will have a specific focus on tabular data models used in finance and insurance, but there will be plenty of opportunity to branch out to other model types and industries. The role has significant customer & user facing elements working on real world problems to help ML teams (R&D and Product within other organizations) improve the quality of their models. In addition you will also work closely with the Safe Intelligence R&D team to help improve the company’s tools based on the challenges you see in your domains of expertise. This can range from inputs to products to working on the product itself. Previous knowledge of Machine Learning Verification isn’t required, but a solid knowledge of existing testing practices, metrics, training, and validation methods are extremely valuable. We’re looking forward to having you on board! Responsibilities As a Safe Intelligence Machine Learning Specialist , you will:
- Work closely with customers and end-users to understand their ML models and help them assess performance. Generally, these will be R&D and product teams at customer organisations.
- Implement prototypes, usecases, and solutions that apply the algorithms developed at Safe Intelligence to address user-specific problems, particularly in the field of tabular data for Finance and Insurance.
- Conduct experiments to evaluate various approaches and weigh their respective trade-offs.
- Coordinate with the research and platform teams to guide future development based on use-case-specific challenges.
- Contribute to the development of an efficient and scalable package for performing verification and robust learning.
- Experience in training, evaluating, and deploying Machine Learning learning models in the Finance or Insurance industries.
- Experience talking to stakeholders in these models to understand their requirements and guiding them through what is and is not possible or desirable in a model.
- Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch.
- Familiarity with common machine-learned model types used for tabular data.
- Fluency in validation and evaluation frameworks and metrics frameworks for machine learning such as Accuracy, Recall, F1 scores, and others.
- An in-depth understanding of Neural Networks and Decision Trees enabling you to train such models to high performance and modify/tune their architecture based on given constraints.
- Familiarity with best practice in Machine Learning workflows and MLOps tools.
- Technical experience in developing non-ML solutions in the Finance or Insurance industries.
- Passionate about helping engineering teams achieve their AI and ML goals.
- Excited about interacting with others and digging in to help solve their problems collaboratively.
- Technical and constantly in a state of learning.
- Able to communicate clearly and efficiently with a variety of audiences, including developers, customers, researchers, partners, and executives.
- Fearless in getting "hands-on" with technology and execution.
- Has a strong understanding of modern software engineering processes.
- Comfortable with ambiguity with a drive for clarity.
- Collaborative with and respectful of others on the team.
- Honest, straightforward, and caring about each other’s well-being.
- 55,000-90,000 GBP / Annual + Stock Option Benefits
- Stock option benefits
- Mentoring, learning, and development allowance
- Regular team social and work events
- Flexible and generous holidays. We work hard and encourage everyone to take time off to recharge and enjoy other aspects of our lives.
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