Senior ML Engineer (Reinforcement Learning)
Role details
Job location
Tech stack
Job description
- Actively contribute to the design, development, testing, and evaluation of data science solutions
- Train and deploy state-of-the-art machine learning and reinforcement learning models
- Build AI systems using Large Language Models
- Build processes for extracting, cleaning and transforming data (SQL / Python)
- Ad-hoc data mining for insights using Python + Jupyter notebooks
- Present insights and predictions in live dashboards using Tableau / PowerBI
- Lead the presentation of findings to clients through written documentation, calls and presentations
- Actively seek out new opportunities to learn and develop
- Be an example of data science best-practice (e.g. Git / Docker / cloud deployment)
- Contribute to proposals for exciting new data science opportunities
- Provide direction and mentoring to more junior data scientists
Requirements
We are looking for a Senior Machine Learning (ML) Engineer who enjoys seeing their work used as part of 'real-life' solutions. Not only will your work directly contribute to our client deliverables, but you will have the opportunity to see the process through from solution design to deployment, working in close collaboration with our wider team.
In short, you'll form an integral part of our close-knit team and will have the opportunity to directly contribute to the continued success of the business. We're looking for someone with a co-operative, can-do attitude who can build high-quality data science solutions., * Experience of presenting technical concepts to stakeholders
- Experience of proactively contributing to the design, development, testing, and deployment of data science and AI solutions
- Experience and understanding of applied machine learning techniques in Python (e.g. xgboost, regression, decision trees)
- Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g. reinforcement learning, deep learning)
- Experience of working collaboratively as part of a data science team, using tools like Git to adhere to established data science and AI best practices
- Experience of using different analysis techniques to draw insight from data, using tools such as Python and SQL
- Excellent Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, NumPy) and at least one deep learning framework
- Excellent communication skills through written reports and presentations
- Effective organisational skills e.g. planning, time management
- Effective problem-solving and analytical skills
- High attention to detail
- Ability to work independently and as part of a team
- Strong foundation in mathematics and statistics
Benefits & conditions
Pulled from the full job description
- Annual leave
- Private medical insurance