Machine Learning Engineer

Job Description

We are seeking a Machine Learning Engineer to join our innovative team in Cambridge. The ideal candidate will have a robust understanding of machine learning algorithms, experience in programming languages such as Python and R, and a passion for building intelligent systems that can transform our business practices. This role involves applying ML techniques to large datasets, collaborating with data scientists, and refining our existing models for better accuracy and efficiency.

Responsibilities

• Create and refine machine learning algorithms to address business challenges.
• Collaborate with data scientists and engineers to optimise data pipelines.
• Provide expertise in statistical analysis and data visualization.
• Assist in deploying machine learning models into cloud environments.
• Contribute to the development of best practices for AI model deployment and maintenance.
• Participate in team meetings to discuss project status and share insights.

Requirements

Education

• Bachelor's degree in a quantitative field
• PhD in Artificial Intelligence is a plus

Experience

• 4+ years of hands-on experience in machine learning

Technical Skills

• Keras
• AutoML

Soft Skills

• Creative problem-solving
• Adaptability

Certifications

• Microsoft Certified: Azure Data Scientist Associate
• Google Professional Machine Learning Engineer

Languages

• English: Fluent

Advantageous

• Familiarity with big data technologies (Hadoop, Spark): Experience with processing large datasets using big data frameworks.
• Experience in natural language processing (NLP): Knowledge of NLP techniques and tools.

Benefits

• Health, dental, and vision insurance
• Generous leave policy including paid parental leave
• Employee assistance programme
• Remote working flexibility post-probation

Company Culture

• Continuous Learning: We believe in ongoing education and skills development, providing resources for professional growth.
• Employee Empowerment: Our employees are empowered to take ownership of their projects, leading to better results.
• Work-Life Balance: We value the well-being of our employees, promoting a healthy work-life balance.