At a Glance
- 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: Competitive salary, remote work, mentorship opportunities, and pathways for career growth.
- Other info: Collaborate with top professionals and shape the future of AI.
- Why this job: Make a real-world impact by applying cutting-edge ML technology to solve industry challenges.
- 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 London 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 London
✨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 Python, PyTorch, and ML systems. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common ML scenarios and be ready to discuss how you've driven production ML pipelines in the past.
✨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 | RAG | Remote, UK in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior ML Engineer role. Highlight your production ML experience, especially with LLMs and Python, to show us you’re the right fit!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about machine learning and how your background makes you a great candidate. Share specific examples of your work that demonstrate your product-focused mindset.
Showcase Your Projects:If you've worked on any relevant projects, whether in a professional or personal capacity, make sure to mention them. We love seeing hands-on experience, especially with AI agents and production ML systems!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from 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. Prepare specific examples that showcase your technical expertise and problem-solving abilities.
✨Showcase Your Product Mindset
This role is all about integrating ML into real products, so be prepared to talk about how you've done this before. Think of instances where your work directly impacted product performance or customer satisfaction. Highlight your ability to think like a product builder.
✨Collaboration is Key
Since you'll be working closely with cross-functional teams, demonstrate your experience in collaborating with product teams. Share examples of how you've successfully integrated ML into customer-facing features and how you communicate technical concepts to non-technical stakeholders.
✨Be Ready to Lead
As a senior engineer, you'll need to show that you can operate autonomously while still aligning with leadership. Prepare to discuss your leadership style and how you've mentored junior engineers in the past. This will show that you're not just a tech whiz but also a team player.
