Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Machine Learning Engineer

SR2 | Socially Responsible Recruitment | Certified B Corporation
Bristol
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer (AI Platform)

Senior AI/ML Engineer

Location:UK Remote

Type:Permanent, Full-time


About the Role

An established tech company is building out its next generation of intelligent software products and is looking for a highly experiencedStaff-level AI/ML Engineerto lead hands-on development of machine learning systems. This is a deeply technical role focused on applied AI, not management or strategy alone.

You’ll work at the intersection of large-scale data processing, generative AI, and cloud infrastructure, contributing directly to the architecture and delivery of smart features across the platform. If you’re passionate about building production-grade AI tools from the ground up, this role offers the opportunity to shape something new in a growing, fast-paced environment.


Key Responsibilities


End-to-End ML Development

  • Own the full lifecycle of machine learning initiatives — from idea to deployment and monitoring.


Hands-On System Design

  • Architect scalable, reliable ML pipelines and APIs, leveraging cloud-native tools and services.


AI Feature Integration

  • Collaborate with engineering and product teams to embed AI-driven functionality into user-facing software.


Technical Leadership

  • Set standards for MLOps, automation, and performance tuning across the engineering team.


Generative AI & LLMs

  • Explore and integrate modern techniques such as large language models and generative architectures.


Mentorship & Collaboration

  • Support peers through code reviews, design discussions, and knowledge sharing.


Scalability & Reliability

  • Solve practical challenges like data quality, explainability, and robust infrastructure for ML.


What You’ll Bring

  • 7+ years of hands-on experience building ML/AI systems in production.
  • 3+ years in a senior technical contributor or team lead role.
  • Advanced Python skills with exposure to common ML frameworks and data libraries.
  • Solid experience working with cloud platforms (ideally AWS) and infrastructure-as-code tools (e.g., Terraform).
  • Understanding of distributed systems, microservices, and modern software architecture.
  • Hands-on experience with LLMs and generative AI models, including tuning and inference.
  • Ability to set up CI/CD pipelines for ML workflows and manage models in a cloud environment.
  • Strong communication and stakeholder engagement skills.
  • A relevant degree in Computer Science, Engineering, or a related field.


Tech Environment

  • Python
  • Java
  • AWS (incl. services for AI/ML)
  • LLM APIs and orchestration tools
  • Terraform, Docker
  • SQL-based databases
  • GitHub Actions and version control tools


Perks & Benefits

  • Competitive compensation
  • 25 days annual leave + bank holidays
  • Flexible remote work policy
  • "Work from anywhere" option (limited days/year)
  • Home office setup budget
  • Enhanced parental leave
  • Pension contribution plan
  • Collaborative and low-ego engineering culture


Important Notes

  • Applicants must be UK-based.
  • Unfortunately, this position is not eligible for visa sponsorship.

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.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has quickly become one of the most transformative forces in modern technology. What began as a subset of artificial intelligence—focused on algorithms that learn from data—has grown into a foundational capability across industries. From voice assistants and recommendation systems to fraud detection and predictive healthcare, machine learning underpins countless innovations shaping daily life. In the UK, demand for ML professionals has surged. Financial services, healthcare providers, retailers, and tech start-ups are investing heavily in ML talent. Roles like Machine Learning Engineer, Data Scientist, and AI Researcher are among the most sought-after and best-paid in the tech sector. Yet we are still only at the start. Advances in generative AI, quantum computing, edge intelligence, and ethical governance are reshaping the field. Many of the most critical machine learning jobs of the next 10–20 years don’t exist yet. This article explores why new careers will emerge, the kinds of roles likely to appear, how today’s jobs will evolve, why the UK is well positioned, and how professionals can prepare.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.