ML Engineer

We are looking for a Machine Learning Engineerwhoenjoys 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.KEY RESPONSIBILITIES:Participate in the design, development, testing, and evaluation of data science solutionsTrain and deploy state-of-the-art machine learning modelsBuild processes for extracting, cleaning and transforming data (SQL / Python)Ad-hoc data mining for insights using Python + Jupyter notebooksPresent insights and predictions in live dashboards using Tableau / PowerBISupport the presentation of findings to clients through written documentation, calls and presentationsAdopt data science best-practice e.g. Git / Docker / cloud deploymentKEY REQUIREMENTS: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 practicesExperience of using different analysis techniques to draw insight from data, using tools such as Python and SQLStrong foundation in mathematics and statisticsProficiency in Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, NumPy)Knowledge of data analysis techniques, such as statistical modelling and visualisation, to draw insight from dataFamiliarity with Git as part of the development processEffective organisational skills e.g. planning, time managementEffective problem-solving and analytical skillsHigh attention to

detailAbility to work independently and as part of a teamUnderstanding of classical machine learning concepts and principles (e.g. xgboost, regression, decision trees)INTERVIEW PROCESS:Stage 1: 20 min video call with a member of the hiring teamStage 2: 45 mins live coding taskStage 3: 90 min F2F interview in our London officeOUR BENEFITS:At ADSP, we believe in rewarding talent and supporting your growth. Here’s what you can look forward to as part of our team:Competitive compensation package including annual performance bonus26 days of annual leave, 8 bank holidays plus your birthday offBUPA Private HealthcareEnhanced family leave£1,000 annual development budgetFlexible hybrid working (2 days a week in our modern Shoreditch office)Remote working from anywhere in the world for up to 4 weeks each yearLatest tech that suits your needs: high-spec Windows machine or a MacBookFree snacks and drinks, and regular team socialsSupportive entrepreneurial environment offering a ton of autonomy and opportunity to work on a variety of projects, technologies and industriesOUR COMMITTMENT TODEI: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 ##### #J-18808-Ljbffr