Senior Machine Learning Engineer

JOB TITLE: SENIOR MACHINE LEARNING ENGINEER

LOCATION: LONDON/REMOTE

SALARY: £80,000 TO £90,000 BASE SALARY PLUS ADDITIONAL BENEFITS

OPPORTUNITY OVERVIEW

Our client is an innovative AI Tech company that are scaling very quickly and are heavily funded. This is an exciting opportunity to be part of something ground-breaking and very unique. Focussing within the Energy space they are leading the way in the sustainability space and have a very exciting proposition for the market. Now in their next stage of growth they are looking for Senior Machine Learning Engineer to be part of their existing ML team to assist in developing the next iterations of their ground breaking solution.

Key Responsibilities:

• Design, develop, and deploy machine learning models: Work on the end-to-end development of machine learning models, from data preprocessing and feature engineering to model training, validation, and deployment.
  
  
• Collaborate with cross-functional teams: Partner with data scientists, software engineers, and product teams to integrate machine learning models into production environments.
  
  
• Optimize and scale ML models: Ensure models are efficient and scalable by optimizing their performance using TensorFlow, JAX, and other frameworks.
  
  
• Manage containerized applications: Use Kubernetes and Docker to containerize and manage ML models, ensuring seamless deployment and scalability in cloud environments.
  
  
• Data manipulation and analysis: Utilize Python libraries such as Pandas for data manipulation and analysis, ensuring that datasets are ready for model training.
  
  
• Continuous learning and experimentation: Stay updated with the latest advancements in machine learning and AI, experimenting with new techniques and tools to improve our models and processes.
  
  
• Model monitoring and maintenance: Monitor the performance of deployed models, troubleshoot issues, and retrain models as necessary to maintain accuracy and relevance
  
  Experience:
  
  
• Programming: Proficiency in Python or C++ is essential for developing and deploying machine learning models.
  
  
• Machine Learning Frameworks: Strong experience with TensorFlow, JAX, and other relevant frameworks for building and optimizing machine learning models.
  
  
• Data Handling: Expertise in using Pandas for data manipulation, analysis, and preparation for machine learning tasks.
  
  
• Containerization: Hands-on experience with Docker and Kubernetes for containerizing applications and managing deployments in cloud environments.
  
  
• Machine Learning Fundamentals: Solid understanding of machine learning algorithms, including supervised and unsupervised learning, neural networks, and deep learning.
  
  
• Software Development: Familiarity with software engineering best practices, including version control (e.g., Git), testing, and documentation.
  
  
• Mathematical Foundations: Strong grasp of mathematics and statistics, particularly in the context of probability, linear algebra, and calculus as they apply to machine learning.
  
  
• Problem-Solving: Proven ability to solve complex problems and apply machine learning techniques to real-world scenarios.
  
  Preferred Qualifications:
  
  
• Cloud Platforms: Experience with cloud platforms such as AWS, Google Cloud, or Azure, particularly for deploying and scaling machine learning models.
  
  
• MLOps: Familiarity with MLOps practices and tools for managing the lifecycle of machine learning models in production.
  
  
• Natural Language Processing (NLP): Experience with NLP techniques and tools, if applicable to the role.
  
  
• Bachelor’s/Master’s/Ph.D. in Computer Science, Engineering, Mathematics, or a related field