Senior Machine Learning Engineer

Senior Machine Learning Engineer
London (Hybrid)
£70,000 - £80,000 per annum (+20% Bonus and Bens)

83DATA are partnered with a dynamic, fast-growing tech company at the forefront of AI and machine learning innovation. Their mission is to leverage cutting-edge machine learning algorithms to drive real-world solutions across various industries, from healthcare to finance. We are looking for a talented Machine Learning Engineer to join the growing team and make a real impact on their AI product offerings.

As a Mid-Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying machine learning models that scale across large datasets. You will work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate advanced ML techniques into our products. This is a hybrid role with a mix of remote work and on-site presence at our London office.

Key Responsibilities:

• Build, train, and optimize scalable machine learning models.
• Collaborate with data scientists and software engineers to integrate models into production systems.
• Design and implement data pipelines to ensure smooth deployment and performance of models.
• Experiment with and evaluate new ML algorithms and technologies.
• Monitor model performance, identifying and resolving bottlenecks and issues.
• Maintain and update documentation for machine learning processes and projects.
• Mentor junior engineers and contribute to the growth of the ML team.

What We're Looking For:

• Proven experience (3-5 years) in machine learning engineering, with a focus on model building and deployment.
• Strong programming skills in Python and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models in a cloud environment.
• Solid understanding of algorithms, data structures, and software engineering best practices.
• Familiarity with data pipeline tools (e.g., Airflow, Spark) and version control systems like Git.
• Strong problem-solving skills and the ability to work both independently and in a collaborative environment.
• Excellent communication skills and a proactive approach to work.
• Experience with natural language processing (NLP), computer vision, or reinforcement learning is a plus.