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 Bolton employer: Enigma
Join a dynamic and innovative startup as a Senior Machine Learning Engineer, where you'll have the opportunity to lead the development of cutting-edge AI solutions from the comfort of your home in the UK. Our collaborative work culture fosters creativity and technical excellence, while offering multiple pathways for professional growth and mentorship opportunities. Be part of a team that is not only shaping the future of AI but also making a tangible impact on real-world challenges.
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 Bolton
✨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 and 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
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Machine Learning Engineer | Python | PyTorch | Machine Learning | Large Language Models | RAG | Remote, UK in Bolton
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Senior Machine Learning Engineer role. Highlight your production ML experience, especially with Python and PyTorch, and don’t forget to mention any work with large language models!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to tell us why you’re passionate about machine learning and how your background makes you a perfect fit for our team. Be sure to connect your past experiences to the specific contributions you can make at StudySmarter.
Showcase Your Projects:If you've worked on relevant projects, whether in a professional or personal capacity, make sure to include them. We love seeing practical applications of your skills, especially if they involve AI agents or LLMs. Links to GitHub or other portfolios can really help us get a sense of your work!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re genuinely interested in joining the StudySmarter 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 Projects
Prepare to share specific examples of projects where you've driven machine learning from experimentation to production. Highlight your role in building evaluation frameworks and how your contributions led to measurable impacts. This will demonstrate your hands-on experience and product-focused mindset.
✨Collaboration is Key
Since this role involves cross-team integration, be ready to discuss how you've collaborated with product teams in the past. Share examples of how you translated technical capabilities into business value, as this will show your ability to work well with others and understand the bigger picture.
✨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 assess if the company aligns with your career goals. Plus, it’s a great way to engage with the interviewers!
