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- Tasks: Lead the development of machine learning infrastructure and drive AI solutions from experimentation to production.
- Company: Join a well-funded startup at the forefront of AI and large language models.
- Benefits: Remote work, competitive salary, and opportunities for professional growth.
- Why this job: Make a real-world impact with cutting-edge AI technology and innovative applications.
- Qualifications: 5+ years in production ML, strong Python skills, and a product-focused mindset.
- Other info: Collaborate with top tech professionals and shape the future of AI.
The predicted salary is between 43200 - 72000 £ per year.
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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Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models [...] employer: Enigma
Contact Detail:
Enigma Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models [...]
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML systems and LLMs. This is your chance to demonstrate your hands-on experience and product-focused mindset to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your past experiences with production ML systems and how you've driven innovation in your previous roles.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives you a better chance of getting noticed by our hiring managers.
We think you need these skills to ace Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models [...]
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with production ML systems and showcases your Python and PyTorch skills. We want to see how you've driven projects from experimentation to production, so don’t hold back on those details!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for machine learning and how you’ve integrated ML into real products. We love seeing a product-focused mindset, so let us know how you think like a builder.
Showcase Your Collaboration Skills: We value cross-functional collaboration, so mention any experiences where you’ve worked closely with product teams or leadership. Highlighting your ability to translate technical capabilities into business value will definitely catch our eye!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Enigma
✨Know Your ML Fundamentals
Brush up on your knowledge of classical and deep learning concepts. Be ready to discuss how these foundations apply to large language models and transformers, as this role heavily relies on them.
✨Showcase Your Production Experience
Prepare specific examples from your past work where you built and scaled ML systems in production. Highlight any challenges you faced and how you overcame them, as this will demonstrate your hands-on experience.
✨Emphasise Collaboration Skills
Since the role involves cross-team integration, be ready to talk about your experiences working with product teams. Share how you translated technical capabilities into business value and improved customer-facing features.
✨Demonstrate a Product-Focused Mindset
Think like a product builder! Prepare to discuss how you've integrated ML systems into real products and the impact they had. This will show that you understand the importance of delivering measurable results.
