Machine Learning Strategist

3 days ago

London, Greater London, United Kingdom Hayward Hawk Full time
Job Overview

Hayward Hawk is a growth-focused company looking for an accomplished Machine Learning Architect to lead the development and implementation of transformative ML solutions.

Estimated salary: £90,000 - £120,000 per annum.

The ideal candidate will have a solid foundation in statistical modelling and algorithm development, as well as extensive experience in machine learning and data science.

Key responsibilities include:

  • Designing and refining machine learning systems to address business needs, ensuring robustness, scalability, and security.
  • Defining and enforcing best practices for end-to-end ML life cycle, from development to production deployment and maintenance.

Additionally, the successful candidate will be responsible for:

  • Leading the strategic vision for the organization's ML capabilities, ensuring alignment with emerging technologies and practices.
  • Collaborating with cross-functional teams to understand business needs, translating them into effective ML solutions.
  • Mentoring a team of data scientists and machine learning engineers, fostering a culture of collaboration and innovation.
  • Providing technical guidance on complex ML challenges and encouraging continuous learning.
  • Partnering with engineering, product, and business teams to integrate ML solutions that add measurable business value.
  • Communicating complex ML concepts to diverse audiences, ensuring clarity and impact.
  • Ensuring all models adhere to regulatory standards and ethical principles, advocating for responsible AI usage.
  • Extensive experience in machine learning and data science is required.
  • Proven expertise in leading ML initiatives and deploying large-scale models is essential.
  • Solid foundation in statistical modelling and algorithm development is necessary.
  • Proficiency in Python and Java, with advanced experience in ML libraries like TensorFlow, PyTorch, and Scikit-learn is required.
  • Skilled in cloud-based deployment (e.g., AWS, Azure, GCP) and experience with big data tools and ETL pipelines is desirable.
  • Ability to operate effectively in fast-paced, agile environments is essential.
  • Background in deep learning, natural language processing, and generative AI is beneficial.
  • Contributions to ML research or open-source initiatives are a plus.

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