At a Glance
- Tasks: Develop and deploy machine learning models to tackle real business challenges.
- Company: Join a leading FTSE 100 organisation with a focus on AI and data.
- Benefits: Competitive daily rate, fully remote work, and a collaborative team environment.
- Other info: Inclusive workplace that values diversity and offers excellent career growth opportunities.
- Why this job: Work with cutting-edge AI technologies and make a significant impact on enterprise-scale projects.
- Qualifications: Strong Python and SQL skills, plus experience in deploying ML solutions.
The predicted salary is between 65250 - 79750 £ per year.
- Machine Learning Engineer
- 6 Month Contract
- £550 to £700 per day Inside IR35
- Fully Remote
The Opportunity
A leading FTSE 100 organisation is seeking a Machine Learning Engineer to join its growing AI and data function.
You'll play a key role in delivering machine learning solutions that support business critical initiatives across the organisation.
Working within a collaborative team of data scientists, analysts and engineers, you'll help build, deploy and enhance AI products in a modern cloud environment.
This is an excellent opportunity for someone who enjoys taking ideas from proof of concept through to production and wants to work with cutting edge AI technologies at enterprise scale
Key Responsibilities
- Develop and deploy machine learning models to solve business challenges.
- Build and maintain scalable ML workflows and pipelines.
- Collaborate with Data Scientists and wider technology teams to productionise models.
- Develop high quality Python code and support CI/CD processes.
- Create and optimise feature engineering and data preparation workflows.
- Monitor model performance and ensure ongoing reliability.
- Produce clear technical documentation and knowledge sharing materials.
- Engage with technical and non-technical stakeholders across the business.
Essential Experience
- Strong Python development skills.
- Strong SQL skills and experience working with large datasets.
- Experience deploying machine learning solutions into production environments.
- Understanding of data processing, transformation and pipeline development.
- Experience building and maintaining end to end ML workflows.
- Solid software engineering and coding best practices.
- Exposure to modern AI and deep learning approaches including NLP and large language model related technologies.
Reasonable Adjustments
Respect and equality are core values to us.
We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all backgrounds and perspectives.
Our success is driven by our people, united by the spirit of partnership to deliver the best resourcing solutions for our clients.
If you need any help or adjustments during the recruitment process for any reason, please let us know when you apply or talk to the recruiters directly so we can support you.
#J-18808-Ljbffr
Machine Learning Engineer employer: Sanderson
Join a forward-thinking team as a DevOps Engineer, where you'll thrive in a fully remote environment that champions innovation and collaboration. With a focus on employee growth, you'll gain invaluable experience working with cutting-edge cloud technologies and automation tools, all while contributing to critical AWS-hosted platforms. Our supportive work culture encourages continuous learning and development, making this an ideal opportunity for those looking to advance their careers in a dynamic setting.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Sanderson before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Sanderson.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Sanderson.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Sanderson, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Sanderson, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Sanderson’s attention and show the tangible impact of your work.
How to prepare for a job interview at Sanderson
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Sanderson.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Sanderson.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Sanderson.
