Machine Learning Architect
3 weeks ago
Principal Machine Learning Architect
Hybrid (Belfast/London)
Full Time
Hayward Hawk are currently recruiting for an accomplished Principal 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 organization's 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:
- Master's 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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