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For Companies At a Glance
- Tasks: Design and deliver innovative ML solutions for exciting cloud projects.
- Company: Join a rapidly growing, employee-focused organisation with prestigious clients.
- Benefits: Enjoy flexible working, generous holidays, excellent healthcare, and performance bonuses.
- Why this job: Work with cutting-edge technology on impactful projects while developing your career.
- Qualifications: Strong ML knowledge, Python proficiency, and cloud deployment experience required.
- Other info: This hybrid role includes occasional travel and social meetups in the UK.
The predicted salary is between 36000 - 60000 £ per year.
Are you an experienced Machine Learning Engineer looking to work on cutting-edge cloud projects for prestigious clients? This organization has experienced continual strong growth since its founding. This exciting role involves designing, building, and delivering complex new solutions within a new function focused on AI and ML.
Benefits
- Along with a highly competitive salary, you will enjoy a comprehensive benefits package and work for an employee-centric organization that values the well-being of its employees, both personally and professionally.
- Generous holiday allowance
- Flexible working options
- Excellent Healthcare and Pension Scheme
- Opportunities for career development and progression with support
- Performance Bonus
About the role
As a mid-to-senior level Machine Learning Engineer, you will create ML models for deployment in the cloud and support Data Engineering, DataOps, and DevOps teams. You will work with the latest technology on highly visible, large-scale projects.
What you’ll bring to the role
- Strong grounding in ML approaches, techniques, and frameworks
- Proficiency in Python, Pandas, TensorFlow, Scikit-learn, Numpy, SciPy
- Experience deploying models to the cloud and working with Azure (Azure DevOps, Azure ML, Azure SQL, ADF, etc.)
- Ability to work with databases such as SQL Server, NoSQL, etc.
- Experience with ETL processes, data pipelines, and DevOps practices
This role is hybrid, requiring occasional presence in one of their UK offices in Scotland or England to maintain company culture through social meetups. You will also travel occasionally to visit clients.
Please apply today for immediate consideration. Bright Purple is an equal opportunities employer: we are proud to work with clients who share our values of diversity and inclusion in our industry.
Machine Learning Engineer employer: Bright Purple
Contact Detail:
Bright Purple Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and AI. Follow industry leaders on social media, read relevant blogs, and participate in online forums to stay updated. This knowledge will not only help you during interviews but also show your genuine interest in the field.
✨Tip Number 2
Network with professionals in the machine learning community. Attend meetups, webinars, or conferences related to AI and ML. Building connections can lead to referrals and insider information about job openings, making it easier for you to land a role with us.
✨Tip Number 3
Showcase your projects and experience on platforms like GitHub or LinkedIn. Highlight any cloud deployment work you've done, especially with Azure. A strong portfolio can set you apart from other candidates and demonstrate your practical skills.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges and ML problem-solving scenarios. Use platforms like LeetCode or HackerRank to sharpen your skills. Being well-prepared will boost your confidence and improve your chances of impressing our hiring team.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning techniques, frameworks, and cloud deployment. Use specific examples that demonstrate your proficiency in Python, TensorFlow, and Azure.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your skills align with their needs, particularly in creating ML models and working with DataOps and DevOps teams.
Showcase Relevant Projects: If you have worked on any notable projects involving machine learning or cloud solutions, be sure to include these in your application. Describe your role and the impact of your contributions.
Highlight Soft Skills: Since this role involves collaboration with various teams, emphasise your communication and teamwork skills. Provide examples of how you've successfully worked in a team environment in previous roles.
How to prepare for a job interview at Bright Purple
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, TensorFlow, and other relevant frameworks. Bring examples of projects where you've successfully deployed ML models to the cloud, particularly using Azure services.
✨Understand the Company’s Focus
Research the organisation's recent projects and their approach to AI and ML. This will help you tailor your responses and demonstrate your genuine interest in their work and culture.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about challenges you've faced in previous roles and how you overcame them, especially in relation to data pipelines and DevOps practices.
✨Emphasise Collaboration and Communication
Since the role involves working with Data Engineering, DataOps, and DevOps teams, highlight your ability to collaborate effectively. Share examples of how you've communicated complex technical concepts to non-technical stakeholders.
