ML Architect

Hybrid (Belfast/London)

Full Time

Hayward Hawk are currently recruiting for an accomplished Machine Learning Architect to lead the development and implementation of transformative ML solutions.

This role focuses on establishing scalable, high-performance ML systems that are aligned with organizational goals and best practices.

The Role:

Architect & Guide ML Solutions

• Design and refine machine learning systems that address business needs, ensuring robustness, scalability, and security.
• Define and enforce best practices for end-to-end ML life cycle, from development to production deployment and maintenance.

Strategy & Innovation

• Lead the strategic vision for the organizations ML capabilities, ensuring alignment with emerging technologies and practices.
• Collaborate with cross-functional teams to understand business needs, translating them into effective ML solutions.

Team Leadership & Mentoring

• Mentor a team of data scientists and machine learning engineers, fostering a culture of collaboration and innovation.
• Provide technical guidance on complex ML challenges and encourage continuous learning.

Stakeholder Collaboration & Communication

• Partner with engineering, product, and business teams to integrate ML solutions that add measurable business value.
• Communicate complex ML concepts to diverse audiences, ensuring clarity and impact.

Ethics & Compliance

• Ensure all models adhere to regulatory standards and ethical principles, advocating for responsible AI usage.

Requirements:

• Masters or Ph.D. in a relevant field (eg, Computer Science, Data Science, Machine Learning).
• Extensive experience in machine learning and data science.
• Proven expertise in leading ML initiatives and deploying large-scale models.
• Solid foundation in statistical modelling and algorithm development.
• Proficiency in Python and Java, with advanced experience in ML libraries like TensorFlow, PyTorch, and Scikit-learn.
• Skilled in cloud-based deployment (eg, AWS, Azure, GCP) and experience with big data tools and ETL pipelines.
• Exceptional problem-solving abilities with a collaborative approach.
• Strong communication and leadership skills, adept at managing and motivating teams.
• Ability to operate effectively in fast-paced, agile environments.
• Background in deep learning, natural language processing, and generative AI.
• Familiarity with MLOps tools and processes.
• Contributions to ML research or open-source initiatives are a plus.

This is an opportunity to shape a vital ML framework within an innovative, growth-focused team.

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