ML Engineer & AI Solutions Architect — Hybrid

Datatonic; London Borough of Harrow; Hybrid; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Holiday: 25 days + bank holidays

Private health insurance

Gym membership discounts

Hybrid work model with WFH allowance

Udemy learning platform access

Auto-enrolment pension after probation

Life Insurance

Income Protection

Cycle to Work Scheme

Tech Scheme

Job summary

Datatonic is shaping the future of AI and data with Google Cloud expertise, driving transformation for clients through ML, data engineering, and analytics. This role focuses on building production-grade ML solutions, with opportunities to lead projects and client discussions.

We seek engineers who combine strong ML fundamentals with excellent communication to deliver innovative AI & cloud-based solutions that meet real business needs. Hybrid work and extensive learning benefits are offered.

Qualifications

• 1-3 years as a Machine Learning Engineer, preferably with a consulting background.
• Proficiency in Python as a backend language, able to deliver production-ready code in CI/CD pipelines.
• Familiarity with cloud platforms such as Google Cloud, AWS, or Azure.
• Foundational software engineering practices.
• Strong knowledge of SQL for data querying and management.
• Experience scaling computations using GPUs or distributed computing.
• Experience exposing ML components through web services or wrappers (Flask).

Responsibilities

• 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.

Skills

Python

CI/CD

SQL

MLOps

Cloud platforms

Data science

Communication

Tools

Flask

Google Cloud

AWS

Azure

Git

Job description

Datatonic is shaping the future of AI and data with Google Cloud expertise, driving transformation for clients through ML, data engineering, and analytics. This role focuses on building production-grade ML solutions, with opportunities to lead projects and client discussions.

We seek engineers who combine strong ML fundamentals with excellent communication to deliver innovative AI & cloud-based solutions that meet real business needs. Hybrid work and extensive learning benefits are offered.