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- Tasks: Build and maintain machine learning infrastructure for an exciting data platform project.
- Company: Join a dynamic team at a leading tech company in Bristol.
- Benefits: Competitive salary, 25 days holiday, and excellent career growth opportunities.
- Why this job: Make a real impact in the world of machine learning and data analytics.
- Qualifications: Experience in ML Ops, Azure, Databricks, and strong problem-solving skills.
- Other info: Collaborative agile environment with opportunities to work on innovative projects.
The predicted salary is between 43000 - 61000 £ per year.
We are looking for a skilled Machine Learning Engineer to join a newly established team working on an exciting data platform project. This is a hands-on role where you will help build and maintain the infrastructure that supports machine learning models in a live environment.
What you will be doing as the Machine Learning Engineer:
- Developing and maintaining API services using Azure and Databricks
- Managing caching layers with Azure Cache (Redis)
- Using Delta Live Tables for data processing and analytics
- Integrating with cloud-based data storage solutions like Snowflake
- Collaborating with cross-functional teams in an agile environment
- Supporting analytics, model deployment, and data-driven decision tools
- Conducting performance, load, and end-to-end testing
- Writing pipeline code and managing deployments via Azure DevOps (GitHub)
What we are looking for from the Machine Learning Engineer:
- Solid experience in ML Ops, particularly with Azure and Databricks
- Familiarity with Postgres, Redis, and Snowflake
- Understanding of Delta Lake Architecture, Docker, and container services
- Experience building and orchestrating APIs
- Strong problem-solving and communication skills
- Bonus: exposure to Azure Functions, Containers, or Insights
Benefits for the Machine Learning Operations Engineer:
- 25 days holiday (rising with service)
Machine Learning Engineer - Bristol employer: Hunter Selection
Contact Detail:
Hunter Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer - Bristol
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure, Databricks, and machine learning models. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and problem-solving abilities. Practice common ML engineering questions and be ready to discuss your experience with APIs, caching layers, and cloud storage solutions.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Machine Learning Engineer - Bristol
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with Azure, Databricks, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on any cool projects related to ML Ops or API development, make sure to mention them. We want to see your hands-on experience and how you've tackled challenges in the past.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be one step closer to joining our awesome team at StudySmarter!
How to prepare for a job interview at Hunter Selection
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Azure, Databricks, and Redis. Brush up on your knowledge of Delta Lake Architecture and Docker, as these will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've implemented machine learning models or built APIs. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand Agile Methodologies
Since the role involves collaborating with cross-functional teams in an agile environment, be prepared to talk about your experience working in agile settings. Share examples of how you’ve contributed to team sprints or adapted to changing requirements.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the role and the company. Inquire about the team dynamics, the data platform project’s goals, or how they measure success in their machine learning initiatives.
