At a Glance
- Tasks: Design and deploy machine learning solutions that tackle real-world business challenges.
- Company: Join Version 1, a forward-thinking tech company focused on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborate with talented engineers and enjoy excellent career advancement opportunities.
- Why this job: Make a tangible impact with cutting-edge ML technologies in a dynamic environment.
- Qualifications: Strong ML fundamentals and hands-on experience in delivering end-to-end ML solutions.
The predicted salary is between 70000 - 90000 £ per year.
hackajob is collaborating with Version 1 to connect them with exceptional professionals for this role.
Design, build, and deploy machine learning solutions that solve real business problems, moving from prototype to production.
Apply traditional ML (e. g., regression/classification/clustering) and deep learning techniques where appropriate, selecting models based on evidence and constraints.
Demonstrate strong ML fundamentals, including the mathematics behind models (probability, statistics, optimisation, linear algebra), and explain trade-offs clearly.
Develop and deploy ML and data science solutions from proof of concept to production Perform data exploration, feature engineering, and model development on large datasets Track experiments, metrics, and model versions (e. g.
MLflow) Collaborate with data engineers and AI engineers to integrate models into platforms Continuously improve models based on performance, feedback, and data drift Qualifications Required Skills additional languages a plus) and experience integrating ML into production systems.
A clear problem-solving mindset: structured thought process, ability to reason through ambiguous requirements, and iterate effectively.
Hands-on experience delivering ML solutions end-to-end, including prototyping, validation, and production/operations.
Experience with Databricks and Spark Hands-on use of MLflow or similar model lifecycle and MLOps frameworks Experience with deep learning frameworks (e. g.
Py Torch) Practical experience with Gen AI / LLMs Exposure to AWS Bedrock
Senior/Lead Machine Learning Engineer employer: Version 1
Version 1 is an exceptional employer that prioritises the well-being and professional growth of its employees. With a strong focus on fostering a collaborative work culture, this role offers unique opportunities to engage with leading Private Sector organisations in the UK & Ireland, driving meaningful impact while enjoying competitive salaries, bonuses, and comprehensive benefits. Join us to be part of a dynamic team that values innovation and personal development.
StudySmarter Expert Advice🤫
We think this is how you could land Senior/Lead Machine Learning Engineer
✨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 Version 1!
✨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 Senior/Lead Machine Learning Engineer at Version 1.
✨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 Version 1.
✨Apply Directly through Our Website
When you find a suitable opening like Senior/Lead Machine Learning Engineer at Version 1, 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 Senior/Lead Machine Learning Engineer
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 Version 1, 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 Version 1. 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 Version 1
✨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 Version 1!
✨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.
