Principal Machine Learning Engineer (London)
New Today
- Translating Requirements: Interpret vague requirements and develop models to solve real-world problems.
- Data Science: Conduct ML experiments using programming languages with machine learning libraries.
- GenAI: Leverage generative AI to develop innovative solutions.
- Optimisation: Optimise machine learning solutions for performance and scalability.
- Custom Code: Implement tailored machine learning code to meet specific needs.
- Data Engineering: Ensure efficient data flow between databases and backend systems.
- MLOps : Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage.
- ML Architecture Design: Create machine learning architectures using Google Cloud tools and services.
- Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven solutions.
- Experience: 5+ years as a Machine Learning Engineer, preferably with a consulting background.
- Programming Skills: Proficiency in Python as a backend language, capable of delivering production-ready code in well-tested CI/CD pipelines.
- Cloud Expertise: Familiarity with cloud platforms such as Google Cloud, AWS, or Azure.
- Software Engineering: Hands-on experience with foundational software engineering practices.
- Database Proficiency :Strong knowledge of SQL for querying and managing data.
- Scalability: Experience scaling computations using GPUs or distributed computing systems.
- ML Integration :Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python).
- Soft Skills: Strong communication and presentation skills to effectively convey technical concepts.
- Scale-up experience.
- Cloud certifications (Google CDL, AWS Solution Architect, etc.).
- Holiday: 25 days plus bank holidays (obviously!)
- Health Perks : Private health insurance (Vitality Health) and Smart Health Services
- Fitness & Wellbeing: 50% gym membership discounts (Nuffield Health, Virgin Active, Pure Gym).
- Hybrid Model: A WFH allowance to keep you comfortable.
- Learning & Growth: Access to platforms like Udemy to fuel your curiosity.
- Pension: (Auto-enrolment after probation period. 3% employer contributions raising 1% per year of service to a max of 10%)
- Life Insurance: (3 x your base salary!)
- Income Protection: (up to 75% of base salary, up to 2 years)
- Cycle to Work Scheme
- Tech Scheme
- Location:
- London
- Job Type:
- FullTime
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