Machine Learning Engineer (London)
This range is provided by Neurolabs. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Neurolabs is looking for a talented Senior Machine Learning Engineer to join our team.
As an ML Engineer at Neurolabs, you will be responsible for developing, implementing, and optimizing Computer Vision models that empower our retail automation solutions. Your expertise will play a crucial role in transforming images into structured data and driving product enhancements that meet our client's needs. We are committed to democratising Computer Vision in the retail space, and your contributions will directly influence the impact of our solutions across various sectors. Responsibilities- Model Development: Design, build, and deploy Large Vision Models (LVMs) for applications focused on enhancing customer experience, workforce efficiencies, and product performance
- Data Preparation: Collaborate with data engineers to collect, preprocess, and curate large visual datasets required for training models, ensuring high-quality data pipelines
- Algorithm Optimization: Iterate on model architectures and hyperparameters to improve performance throughput while maintaining efficiency
- Collaboration: Work closely with cross-functional teams, including software engineers, product managers, and platform engineers, to deliver integrated Computer Vision solutions
- Performance Monitoring: Monitor live models and performance metrics, troubleshoot issues, and implement updates as necessary to ensure optimal performance
- Continuous Learning: Stay updated with the latest research and advances in machine learning and computer vision. Drive innovation by applying new techniques and methods to our projects
- Educational Background:
- Master's degree or equivalent experience in Computer Science, Data Science, or a related field with a strong focus on machine learning
- Professional Experience:
- 5+ years of hands-on experience deploying Computer Vision models in production environments
- Strong proficiency in Python
- Experience with cloud environments (AWS, GCP) and tools for ML model deployment (Docker, Kubernetes, etc.)
- Technical Skills:
- In-depth understanding of computer vision techniques, including image classification, detection, and segmentation
- Familiarity with Large Vision Models is a big plus
- Knowledge of SQL and experience working with large datasets and data manipulation
- Problem-Solving Abilities:
- Strong analytical skills, capable of troubleshooting complex problems
- Proven ability to innovate and adapt to changing technologies
- Excellent collaboration and communication skills, capable of working effectively within a team
- Inclusive and Supportive Culture - We're building a team where everyone feels seen, heard, and valued—collaboration, psychological safety, and kindness are baked into how we work
- Hybrid‑First Model - Strike the perfect balance: work from home or collaborate in our London office - whatever fuels your productivity and well‑being
- Equity Share Options - Your hard work powers our mission - and you'll share in the company's success through equity ownership
- Generous Time Off - Enjoy up to 34 days of annual leave and UK bank holidays to recharge, explore or just unwind
- Annual Retreats & Team Workations - Once a year, we bring the team together at our company wide retreat or more regularly during our team workation to bond, innovate and refresh outside the office environment
- All‑Inclusive Private Health - Our private medical cover includes mental health support, dental and optics, plus travel insurance (for both personal adventures and work trips)
- Pension Plan - We help you invest in your future with a competitive employer‑contributed pension scheme.
- Seniority levelMid-Senior level
- Employment typeFull-time
- IndustriesIT Services and IT Consulting
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#J-18808-Ljbffr- Company
- Neurolabs
- Location
- London, UK
Hybrid / WFH Options - Employment Type
- Full-time
- Posted
- Company
- Neurolabs
- Location
- London, UK
Hybrid / WFH Options - Employment Type
- Full-time
- Posted