ML Engineer

We are looking for a Machine Learning 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.

If this sounds like you, we can't wait to hear from you!

• Participate in the design, development, testing, and evaluation of data science solutions
• Train and deploy state‑of‑the‑art machine learning 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
• Support the presentation of findings to clients through written documentation, calls and presentations
• Adopt data science best‑practice e.g. Git / Docker / cloud deployment

• Experience with applied machine learning techniques in Python (e.g. xgboost, regression, decision trees)
• 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
• Strong foundation in mathematics and statistics
• Proficiency in Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, Num Py)
• Knowledge of data analysis techniques, such as statistical modelling and visualisation, to draw insight from data
• Familiarity with Git as part of the development process
• 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
• Understanding of classical machine learning concepts and principles (e.g. xgboost, regression, decision trees)

• Experience of contributing to the design, development, testing, and deployment of data science and AI solutions
• Basic knowledge of database systems (e.g., SQL, No
  
  SQL) and familiarity with cloud platforms (e.g., AWS, GCP, Azure)
• Excellent communication skills through written reports and presentations

Stage 1: 20 min video call with a member of the hiring team

Stage 2: 45 mins live coding task

Stage 2: 90 min F2F interview in our London office

At ADSP, we are committed to fostering an inclusive hiring process and believe in creating an environment where all candidates have equal opportunities to succeed. If you require any reasonable adjustments during the application or interview process, please do not hesitate to reach out to us at careers