Senior Machine Learning Engineer

About the Role

Our client is seeking a highly skilled and innovative Senior Machine Learning Engineer to join their dynamic team in London . This pivotal role involves designing, developing, and deploying cutting-edge machine learning models and systems that drive our client's core product offerings. You will be instrumental in shaping the future of artificial intelligence within the company, working on challenging problems that require a deep understanding of statistical modeling, algorithms, and data structures. This position offers a unique opportunity to collaborate with world-class researchers and engineers, pushing the boundaries of what's possible in the field of AI and contributing to the strategic direction of advanced technology initiatives, fostering a culture of continuous learning and technological excellence.

Key Responsibilities

• Design, build, and maintain scalable machine learning pipelines and infrastructure for training, evaluation, and deployment.
• Develop and implement novel ML algorithms and models to solve complex business problems in areas such as natural language processing, computer vision, or recommendation systems.
• Collaborate with data scientists and software engineers to integrate ML models into production systems and applications.
• Conduct rigorous experimentation and performance analysis to optimize model accuracy, efficiency, and robustness.
• Stay abreast of the latest advancements in AI/ML research and technologies, and propose innovative solutions.
• Mentor junior engineers and contribute to the team's technical growth and best practices in London .

  Requirements
• Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Proven experience (5+ years) in developing and deploying production-level machine learning models.
• Strong programming skills in Python and proficiency with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Expertise in data preprocessing, feature engineering, model selection, and hyperparameter tuning.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Excellent analytical, problem-solving, and communication skills.

  Benefits
• Competitive salary and performance-based bonuses.
• Comprehensive health, dental, and vision insurance plans.
• Generous paid time off, including holidays and personal days.
• Opportunities for professional development, including conferences and training.
• Hybrid work model offering a blend of in-office and remote flexibility in London .
• Access to state-of-the-art technology and research facilities.