At a Glance
- Tasks: Design and optimise machine learning models, owning the entire ML lifecycle.
- Company: Join a forward-thinking tech company in vibrant Bristol.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make an impact with cutting-edge ML technologies and mentor the next generation of engineers.
- Qualifications: Proven experience in ML model development and strong Python skills required.
The predicted salary is between 60000 - 80000 € per year.
What you will do as a Senior ML Engineer:
- Design, build, and optimise machine learning models, including NLP, computer vision, and predictive analytics.
- Own the ML lifecycle from data preparation through training, evaluation, and deployment.
- Implement and maintain MLOps workflows for continuous integration and delivery of ML models.
- Collaborate with Data Engineers and DevOps teams to ensure production readiness and scalability.
- Contribute to architecture decisions for ML pipelines and data flows.
- Apply secure coding and configuration practices in line with compliance standards.
- Mentor junior engineers and share best practices across the team.
- Support innovation by researching emerging ML techniques and tools.
What you’ll bring:
- Proven experience developing and deploying machine learning models in production environments.
- Proven experience with the OpenCV framework and various object detection models, including YOLO, RCNN, and Vision models, along with a clear understanding of when to apply each model.
- Proficiency with object detection concepts.
- Experience in video analysis, particularly optical flow and object tracking.
- Solid knowledge of Optical Character Recognition (OCR) models, with the ability to fine-tune these models using custom datasets.
- An understanding of how to measure the accuracy of text extractions through metrics like Character Error Rate (CER) and Word Error Rate (WER) is also crucial.
- Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch).
- Understanding of ML architectures, hyperparameter tuning, and performance optimisation.
- Experience with MLOps tools and CI/CD pipelines.
- Familiarity with data engineering concepts (ETL, data pipelines, SQL).
- Ability to analyse complex data and communicate insights effectively.
- Strong problem-solving skills and attention to detail.
- Excellent collaboration and stakeholder engagement skills.
Core areas (must have):
- ML Development Expertise: Hands-on experience building and deploying ML models.
- Lifecycle Ownership: Ability to manage ML workflows from design to production.
- Tool Proficiency: Skilled in Python, ML frameworks, and MLOps tooling.
- Data Engineering Awareness: Understanding of data pipelines, warehousing, and integration.
Senior Machine Learning Engineer in Bristol employer: Energy Jobline ZR
As a Senior Machine Learning Engineer in Bristol, you will thrive in a dynamic and innovative work culture that prioritises collaboration and continuous learning. The company offers excellent employee growth opportunities through mentorship and exposure to cutting-edge ML techniques, alongside competitive benefits that support work-life balance. With a focus on impactful projects and a commitment to professional development, this role provides a meaningful and rewarding career path in the heart of a vibrant tech community.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer in Bristol
✨Tip Number 1
Network like a pro! Reach out to your connections in the ML field, attend meetups, and join online forums. 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 machine learning projects, especially those involving NLP, computer vision, and predictive analytics. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with MLOps workflows and how you've optimised ML models in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Machine Learning Engineer in Bristol
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with machine learning models, especially in NLP and computer vision. We want to see how you've owned the ML lifecycle and any MLOps workflows you've implemented.
Showcase Your Projects:Include specific projects where you've developed and deployed ML models. Mention the frameworks you used, like TensorFlow or PyTorch, and any object detection models you've worked with. This helps us see your hands-on experience!
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured applications that communicate your skills and experiences effectively. Avoid jargon unless it's relevant to the role.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you're keen on joining our team!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've worked with, especially those mentioned in the job description like YOLO and RCNN. Be ready to explain when to use each model and share specific examples of how you've implemented them in production.
✨Showcase Your MLOps Knowledge
Since MLOps is a key part of the role, brush up on your experience with CI/CD pipelines and MLOps tools. Prepare to discuss how you've managed the ML lifecycle, from data preparation to deployment, and any challenges you've faced along the way.
✨Demonstrate Collaboration Skills
Collaboration is crucial for this position, so think of examples where you've worked closely with Data Engineers or DevOps teams. Highlight how you ensured production readiness and scalability in your projects, and be prepared to discuss how you handle stakeholder engagement.
✨Prepare for Technical Questions
Expect technical questions that test your understanding of concepts like Optical Character Recognition (OCR) and performance metrics like Character Error Rate (CER). Brush up on these topics and be ready to explain how you've applied them in your work.
