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 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

KEY 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 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, NumPy)

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)

INTERVIEW PROCESS:

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

Stage 2: 45 mins live coding task

Stage 3: 90 min F2F interview in our London office

OUR 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 bonus

26 days of annual leave, 8 bank holidays plus your birthday off

BUPA Private Healthcare

Enhanced family leave

£1,000 annual development budget

Flexible hybrid working (2 days a week in our modern Shoreditch office)

Remote working from anywhere in the world for up to 4 weeks each year

Latest tech that suits your needs: high-spec Windows machine or a MacBook

Free snacks and drinks, and regular team socials

Supportive entrepreneurial environment offering a ton of autonomy and opportunity to work on a variety of projects, technologies and industries

OUR 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

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