Senior Machine Learning Engineer

• 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.

Do you have experience in Web services?, To be successful, you will need strong ML & Data Science fundamentals and will know the right tools and approach for each ML use case. You'll be comfortable with model optimisation and deployment tools and practices. Furthermore, you'll also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud., * Experience: 4-7 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.

Bonus Points If You Have:

• Scale-up experience.
• Cloud certifications (Google CDL, AWS Solution Architect, etc.).

Pulled from the full job description

• Life insurance
• Company pension
• Private medical insurance
• Cycle to work scheme
• Tech scheme
• Discounted gym membership

At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world., Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow. At Datatonic, innovation isn't just encouraged - it's embedded in everything we do. If you're ready to inspire change and deliver value at the forefront of data and AI, we'd love to hear from you!