Principal Machine Learning Engineer

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.

As a Principal Machine Learning Engineer (equivalent to a Lead Engineer in many organisations), you’ll be a visionary leader
, driving technical excellence and innovation. You’ll not only engineer beautiful code in Python but also set the standard for high-quality engineering and best practices across production software and rapid prototypes.

This is a hands-on technical role with significant leadership responsibilities
. You will lead projects, mentor junior and senior engineers, and actively drive client discussions. Your responsibilities will involve building trusted relationships with prospects, defining strategic approaches to use machine learning to solve complex problems, overseeing project scoping, and ensuring the successful, high-impact delivery of these engagements. You will be a key voice in shaping our technical direction and fostering a culture of innovation.

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 will also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI & Cloud.

• Translating Requirements: Interpret ambiguous and complex requirements, translating them into clear technical specifications and leading the development of innovative models to solve real-world, high-impact problems.

• Data Science: Lead and oversee ML experiments, driving the selection of appropriate programming languages and machine learning libraries, and establishing best practices for experimental design and analysis.

• GenAI: Pioneer the application of generative AI to develop groundbreaking and innovative solutions, setting technical direction and strategy.

• Optimisation: Architect and implement advanced optimisation strategies for machine learning solutions, ensuring peak performance, scalability, and cost-efficiency across large-scale systems.

• Custom Code: Design and implement highly tailored, complex machine learning code to meet unique and challenging business needs, often involving novel approaches.

• Data Engineering: Own and define the strategy for efficient data flow between complex databases and distributed backend systems, ensuring data integrity and accessibility for ML initiatives.

• MLOps: Establish and champion MLOps best practices, leading the automation of ML workflows, and driving advancements in testing, reproducibility, and robust feature/metadata storage solutions.

• ML Architecture Design: Lead the design and evolution of sophisticated machine learning architectures, leveraging advanced Google Cloud tools and services to build resilient and scalable platforms.

• Engineering Software for Production: Drive the development and deployment of production-grade software for machine learning and data-driven solutions, ensuring high standards of code quality, reliability, and maintainability.

• Experience: 5+ years of progressive experience as a Machine Learning Engineer, with a significant portion in a leadership or consulting capacity, demonstrating a proven ability to lead complex projects and teams. This includes experience in technical leadership, guiding architectural decisions, and potentially people leadership or mentorship.

• 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…