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Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models [...]Enigma • London, England, United Kingdom
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Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models [...]

Enigma
  • GB
    London, England, United Kingdom
  • GB
    London, England, United Kingdom
Apply Now

About

Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models | RAG | Remote, UK 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
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  • London, England, United Kingdom

Languages

  • English
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