Principal Machine Learning Architect

Hayward Hawk
London
1 year ago
Applications closed

Related Jobs

View all jobs

Principal Data Analyst

Principal Data Engineer

Principal Data Engineer (GCP)

Principal Data Analyst

Principal Data Engineer

Principal Data Engineer (MS Azure)

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.

J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.