At a Glance
- Tasks: Lead the development of machine learning infrastructure and drive AI solutions from concept to production.
- Company: Join a well-funded startup at the forefront of AI innovation.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Other info: Collaborate with top tech professionals and shape the future of AI.
- Why this job: Make a real-world impact by applying cutting-edge ML technologies.
- Qualifications: 5+ years in production ML, strong Python skills, and a product-focused mindset.
The predicted salary is between 70000 - 90000 £ per year.
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 in Leigh employer: Enigma
Join a pioneering startup as a Senior Machine Learning Engineer, where you'll lead the charge in transforming cutting-edge AI research into impactful solutions. Enjoy a collaborative work culture that values innovation and autonomy, with ample opportunities for professional growth and mentorship. Work remotely from the UK while contributing to breakthrough applications of large language models, making a real-world impact in the AI landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models | RAG | Remote, UK in Leigh
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ML systems or LLMs. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and product-focused questions. Be ready to discuss how you've integrated ML into real products and the impact it had. We want to see your thought process!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team and making a real-world impact with AI.
We think you need these skills to ace Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models | RAG | Remote, UK in Leigh
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 machine learning projects from experimentation to production, so be specific about your contributions!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with our mission at StudySmarter. Don't forget to mention any experience you have with large language models or AI agents.
Showcase Your Projects:If you've worked on any relevant projects, make sure to include them in your application. We love seeing real-world applications of your skills, especially if they involve ML pipelines or cross-team collaboration. Share links or descriptions that highlight your impact!
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for this exciting opportunity to join our team!
How to prepare for a job interview at Enigma
✨Know Your Stuff
Make sure you brush up on your Python and PyTorch skills. Be ready to discuss your experience with large language models and how you've scaled production ML systems in the past. They’ll want to see that you can not only talk the talk but also walk the walk.
✨Showcase Your Product Mindset
Prepare examples of how you've integrated ML systems into real products. Think about specific projects where your work had a measurable impact. This role is all about driving product innovation, so demonstrating your product-focused mindset will set you apart.
✨Collaboration is Key
Since this position involves cross-team integration, be ready to discuss how you've collaborated with product teams in the past. Highlight any experiences where you translated technical capabilities into business value, as this will resonate well with the interviewers.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's vision for AI and how they plan to scale their ML infrastructure. This shows your genuine interest in the role and helps you gauge if the company aligns with your career goals. Plus, it’s a great way to demonstrate your strategic thinking!
