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- Tasks: Design and deploy cutting-edge machine learning models for computer vision applications.
- Company: Join a revolutionary Deep Tech startup transforming the CPG industry.
- Benefits: Competitive salary, full-time role, and opportunities for professional growth.
- Why this job: Be at the forefront of technology and make a real impact in the industry.
- Qualifications: 4+ years in machine learning with strong computer vision expertise.
- Other info: Collaborative environment with a focus on innovation and performance.
The predicted salary is between 48000 - 72000 £ per year.
Please only apply if you have previous experience working on Large Vision Models or Large Language Models.
We have partnered with a Deep Tech Seed Stage startup, who are revolutionising the CPG industry by implementing Image recognition. The team are looking for someone with deep Computer Vision knowledge.
- Model Development: Design, build, and deploy machine learning models for computer vision applications.
- Algorithm Optimization: Iterate on model architectures and hyperparameters to improve performance throughput while maintaining efficiency.
- Collaboration: Work closely with cross-functional teams.
- Performance Monitoring: Monitor live models and performance metrics.
Requirements:
- 4+ years of hands-on experience deploying machine learning models in production environments.
- In-depth understanding of computer vision techniques, including image classification, detection, and segmentation.
- Familiarity with reinforcement learning methods is a plus.
Senior Machine Learning Engineer employer: Few&Far
Contact Detail:
Few&Far Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work with large vision models or language models. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects related to computer vision. This could be anything from model development to algorithm optimisation – let your work speak for itself!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with deploying machine learning models and how you’ve tackled challenges in performance monitoring.
✨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
Some tips for your application 🫡
Show Off Your Experience: Make sure to highlight your previous work with Large Vision Models or Large Language Models. We want to see how your experience aligns with our needs, so don’t hold back on the details!
Tailor Your Application: Customise your CV and cover letter to reflect the specific skills and experiences mentioned in the job description. We love seeing candidates who take the time to connect their background to what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant to the role. Let us see your expertise without the fluff!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Few&Far
✨Know Your Models Inside Out
Make sure you can discuss your experience with Large Vision Models and Large Language Models in detail. Be prepared to explain the architectures you've worked with, the challenges you faced, and how you optimised them for performance.
✨Showcase Your Collaboration Skills
Since the role involves working closely with cross-functional teams, think of examples where you've successfully collaborated with others. Highlight how you communicated complex technical concepts to non-technical team members.
✨Prepare for Technical Questions
Brush up on key computer vision techniques like image classification, detection, and segmentation. You might be asked to solve a problem on the spot, so practice explaining your thought process clearly and concisely.
✨Demonstrate Your Monitoring Experience
Be ready to discuss how you've monitored live models and what metrics you focused on. Share specific examples of how you identified issues and improved model performance based on those insights.