Principal Machine Learning Architect
Posted 16 hours 28 minutes ago by Hayward Hawk
Permanent
Not Specified
Other
London, United Kingdom
Job Description
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 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.