Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models | RAG | Remote, UK and EU
Summary of the Role:
As a Senior ML Engineer, you'll be the technical leader driving machine learning infrastructure from experimentation to production, ensuring AI-powered solutions deliver measurable impact for customers worldwide. This is a unique opportunity to join as one of the early engineering team members of a well-funded startup building breakthrough applications of large language models (LLMs) and AI agents.
You'll take full ownership of evaluation frameworks, production ML pipelines, and cross-team ML integration, working closely with company leadership and product teams to transform cutting-edge AI research into robust, scalable solutions. Your success will be measured by agent performance improvements and product innovation impact, not just technical metrics. This role is ideal for a hands-on ML engineer who has scaled production ML systems, thinks like a product builder, and wants to drive the productionization of LLMs and ML to solve real-world problems.
Your Contributions:
• Build Production-Grade Evaluation Systems:
Design and implement evaluation frameworks that measure performance, track improvements, and ensure consistent value delivery.
• Drive Experimentation-to-Production Pipeline:
Own the ML lifecycle from prototype to production, enabling rapid iteration while maintaining reliability.
• Enable Cross-Team ML Integration:
Collaborate with product teams to integrate ML into customer-facing features.
• Optimize AI Agent Performance:
Improve systems through experimentation, prompt engineering, and architecture enhancements.
• Scale ML Infrastructure:
Develop foundational systems, monitoring, and tooling to support rapid growth.
• Partner with Leadership:
Work closely with senior leadership while operating with high autonomy.
• Mentor Through Excellence:
Provide guidance and mentorship to junior ML engineers.
What You Need to Be Successful:
• Production ML Experience:
5+ years building and scaling ML systems in production.
• Neural Networks Foundation:
Strong background in classical and deep learning before specializing in LLMs and transformers.
• Product-Focused Mindset:
Track record of integrating ML systems into real products.
• Multi-Company Perspective:
Experience across startups and/or scale-ups.
• Technical Versatility:
Strong Python skills and adaptability across frameworks and tools (e.g., LangChain, workflow orchestration).
• Self-Directed Leadership:
Ability to operate autonomously while aligned with leadership.
• Cross-Functional Collaboration:
Experience translating technical capabilities into business value.
Nice to Haves:
• Experience with AI agents, LLMs, or generative AI applications
• Domain knowledge in cybersecurity or related fields
• Background at ML-first companies
• Experience with modern MLOps and cloud ML infrastructure
• Track record of optimizing model performance and costs
Why Join:
• Real-World AI Impact:
Apply ML to solve significant industry challenges.
• Technical Leadership:
Shape infrastructure and systems that will scale.
• Expert Team Partnership:
Collaborate with experienced professionals from top tech companies and scale-ups.
• Build the AI-Native Future:
Establish ML practices and standards in a rapidly evolving field.
• Multiple Growth Pathways:
Opportunities for leadership, technical specialization, or senior IC roles.
• Breakthrough Technology:
Work at the intersection of generative AI and practical applications.
Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models | RAG | Remote, UK and EU
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