Machine Learning Engineer

About the role

As a Machine Learning Engineer at Datatonic you will write clean, production‑ready Python code and champion high‑quality engineering practices. You will work on both rapid prototypes and robust, scalable solutions while engaging directly with clients to shape AI projects.

Key responsibilities

• Build trusted relationships with prospects and lead client discussions on AI solutions.
• Interpret vague requirements and develop machine learning models to solve real‑world problems.
• Conduct ML experiments using Python libraries and leverage generative AI for innovative outcomes.
• Optimize models for performance, scalability and deploy them using MLOps pipelines.
• Design end‑to‑end ML architectures on Google Cloud and integrate them via web services such as Flask.
• Ensure efficient data flow between databases and backend systems.

Required profile

• 1‑3 years experience as a Machine Learning Engineer, preferably in a consulting environment.
• Strong communication and presentation skills to convey technical concepts to business stakeholders.

Required skills

• Proficiency in Python for production‑grade code.
• Experience with cloud platforms (Google Cloud, AWS, Azure).
• SQL for data querying and management.
• Knowledge of GPU or distributed computing for scaling workloads.
• Familiarity with exposing ML models via web services (e.g., Flask).
• Understanding of CI/CD pipelines and MLOps practices.

What we offer

• 25 days holiday plus bank holidays.
• Private health insurance and Smart Health Services.
• 50% discount on gym memberships (Nuffield Health, Virgin Active, Pure Gym).
• Hybrid working model with a work‑from‑home allowance.
• Learning budget via Udemy.
• Pension auto‑enrolment with employer contributions.
• Life insurance (3× salary) and income protection (up to 75% salary).
• Cycle‑to‑Work and Tech schemes.