Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models [...]
New Today
Overview
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.
Location & Availability
Remote, UK
London, England, United Kingdom
Dates and locations referenced reflect job postings history and are for context only.
- Location:
- United Kingdom
- Salary:
- £80,000 - £100,000
- Job Type:
- FullTime
- Category:
- IT & Technology
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