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Datatonic

Senior Machine Learning Engineer

Reposted 9 Days Ago
Be an Early Applicant
In-Office
London, Greater London, England
Senior level
In-Office
London, Greater London, England
Senior level
As a Senior Machine Learning Engineer, you will develop models, optimize existing solutions, automate ML workflows, and contribute to engineering production-ready software using machine learning and cloud tools.
The summary above was generated by AI
Shape the Future of AI & Data with Us

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 Platform. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.

Your Mission

As a Senior Machine Learning Engineer, you'll be a key individual contributor, engineering beautiful code in Python and taking pride in what you produce. You'll advocate for high-quality engineering and best practices in production software and rapid prototypes.

While this is a hands-on technical role, you'll also contribute to client discussions and help scope projects, applying machine learning creatively to solve problems.

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.

What You’ll Do

  • Translating Requirements: Interpret well-defined requirements and develop models to solve specific problems.

  • Data Science: Conduct ML experiments using programming languages with machine learning libraries, focusing on established methodologies.

  • GenAI: Leverage generative AI to develop innovative solutions.

  • Optimisation: Optimise existing machine learning solutions for performance and scalability under guidance.

  • Custom Code: Implement tailored machine learning code for specific features or modules.

  • Data Engineering: Contribute to ensuring 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.

What You’ll Bring

  • Experience: Multiple years of experience as a Machine Learning Engineer, preferably with a consulting background, demonstrating a strong track record of successful project delivery on individual contributions.

  • 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 skills to effectively convey technical concepts to team members and stakeholders.

Bonus Points If You Have:
  • Scale-up experience.

  • Cloud certifications (Google CDL, AWS Solution Architect, etc.).

What’s in It for You?

We believe in empowering our team to thrive, with benefits including:

  • 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

Why Datatonic?

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!

Are you ready to make an impact?

Apply now and take your career to the next level.

Top Skills

AWS
Azure
GCP
Python
SQL
HQ

Datatonic London, England Office

1 Canada Square, London, United Kingdom, E14 5AB

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