Lead ML Engineer in London

Lead ML Engineer in London

London Full-Time 36000 - 60000 £ / year (est.) Hybrid
A

At a Glance

  • Tasks: Lead the design and delivery of innovative AI solutions for diverse clients.
  • Company: Join a forward-thinking tech company with a collaborative and supportive culture.
  • Benefits: Competitive salary, performance bonuses, generous leave, and a £1,000 development budget.
  • Other info: Enjoy hybrid working, work from abroad options, and a fun team environment.
  • Why this job: Make a real-world impact with cutting-edge machine learning and AI technologies.
  • Qualifications: Degree in a quantitative field and experience in leading complex data science projects.

The predicted salary is between 36000 - 60000 £ per year.

We are looking for a Lead ML Engineer to drive technical project delivery, guiding teams to develop robust, scalable machine learning and generative AI solutions crafted for our clients. If you enjoy seeing the impact of your work in real-world applications, this role is perfect for you. Not only will you play a critical part in client deliverables, but you will also have the chance to explore and apply cutting‐edge machine learning techniques across a variety of industries and geographies, delivering projects end‐to‐end from initial design to production deployment. You will form an integral part of our close‐knit team, directly contributing to the ongoing success of the business. We are seeking someone with a collaborative, can‐do attitude who has a passion for delivering high‐quality solutions and is comfortable leading the delivery of innovative, full‐stack data science and machine learning projects.

KEY RESPONSIBILITIES:

  • Lead the design, development, testing, and evaluation of AI solutions for the successful delivery of several, simultaneous client projects
  • Build strong client relationships and lead project centred client interactions
  • Oversee the delivery of high‐quality code and successful project outcomes
  • Build processes for extracting, cleaning and transforming data (SQL / Python)
  • Build AI systems using Large Language Models
  • Actively seek out new opportunities to learn and develop
  • Be an example of data science and software engineering best‐practice e.g. Git / Docker / cloud deployment
  • Write proposals for exciting new commercial opportunities
  • Line manage and provide career mentorship to other data scientists
  • Manage project delivery teams
  • Collaborate with stakeholders to understand business needs and develop technical strategies
  • Take ownership of the development and implementation of internal processes and policies
  • Proactive thought leadership to encourage development and promote ADSP
  • Contribute to the development and deployment of delivery solutions
  • Ad‐hoc data mining for insights using Python + Jupyter notebooks
  • Train and deploy state‐of‐the‐art machine learning and reinforcement learning models

KEY REQUIREMENTS:

  • Degree in a quantitative field such as mathematics, statistics or data science
  • Experience of strong communication skills, including leading meetings and presenting technical concepts to stakeholders
  • Experience of successfully leading complex data science and AI projects, including a holistic understanding of the data science development process, from design through to deployment, and associated project management and risks
  • Experience completing code reviews in Python and SQL through Git, and applied other best practices to technical projects
  • Experience of using SQL and databases (SQL Server, Postgres etc), as well as a cloud platform for development
  • 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, LLMs)
  • Experience of using different analysis techniques to draw insight from complex data
  • Understanding of Docker implementations including Docker storage and volumes
  • Ability to successfully manage delivery teams
  • Understanding of Python advanced concepts including Object Oriented Programming (OOP), Concurrency, decorators, recursion
  • Ability to work with external stakeholders, including management of expectations understanding of business goals and balancing project requirements
  • Ability to think strategically and make complex decisions
  • Effective organisational skills e.g. planning, time management
  • Effective problem‐solving and analytical skills, with high attention to detail
  • Familiarity of the most state‐of‐the‐art AI developments and trends
  • Excellent Python, including relevant libraries for data analysis and machine learning (e.g. sklearn, Pandas, NumPy) and at least one deep learning framework

Company Benefits:

  • Market Competitive Compensation: We benchmark salaries regularly to ensure you're paid fairly for the impact you make
  • Annual Performance Bonus: Your hard work deserves recognition, and we reward it with a bonus tied to your performance and our success
  • Generous Time Off: You'll get 26 days of annual leave plus bank holidays, with additional enhanced sick pay when you need to rest and recover
  • Enhanced Family Leave: We offer enhanced maternity and paternity leave to help you focus on what matters most when your family grows
  • Annual Development Budget: We're serious about growth. You'll get a dedicated £1,000 budget to spend on courses, conferences, coaching, or anything else that helps you level up
  • Private Healthcare: Your health matters. Our comprehensive private health plan includes mental health support and fast access to care when you need it
  • Snacks & Socials: From free drinks and snacks in the office to regular team socials, quizzes, and spontaneous celebrations, we believe fun fuels great teamwork.
  • Work From Abroad: Want a change of scenery? You can work from anywhere in the world for up to a month each year
  • Hybrid Working: We work from the office two days a week to stay connected and collaborate face‐to‐face, with flexibility the rest of the time

Lead ML Engineer in London employer: Applied Data Science Partners

Applied Data Science Partners is an exceptional employer that fosters a collaborative and innovative work culture, perfect for Senior Machine Learning Engineers looking to make a significant impact. With a generous £1k development budget, employees are encouraged to pursue continuous learning and growth, while the hybrid role offers flexibility to balance work and personal life. Located in a vibrant area, the company provides unique opportunities to engage with diverse client projects, ensuring that every team member contributes to meaningful data science outcomes.

A

Contact Details:

Applied Data Science Partners Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead ML Engineer in London

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Applied Data Science Partners!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead ML Engineer at Applied Data Science Partners.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Applied Data Science Partners.

✨Apply Directly through Our Website

When you find a suitable opening like Lead ML Engineer at Applied Data Science Partners, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Lead ML Engineer in London

Machine Learning
Generative AI
Project Management
Client Relationship Management
Data Extraction and Transformation (SQL, Python)
Large Language Models (LLMs)
Data Science Best Practices (Git, Docker, Cloud Deployment)

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Applied Data Science Partners, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Applied Data Science Partners. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Applied Data Science Partners

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Applied Data Science Partners!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.