Staff Machine Learning Platform/Ops Engineer

Staff Machine Learning Platform/Ops Engineer

Full-Time 60000 - 84000 € / year (est.) No home office possible
Preply

At a Glance

  • Tasks: Design and evolve Preply's ML platform for seamless production deployment.
  • Company: Join a dynamic Ed-Tech company with a collaborative culture.
  • Benefits: Generous learning allowance, competitive salary, equity, and health insurance.
  • Other info: Diverse environment with excellent growth opportunities and a focus on inclusion.
  • Why this job: Make a real impact in the world of language learning and teaching.
  • Qualifications: 8+ years in Data/ML platforms, strong cloud services knowledge, and mentoring skills.

The predicted salary is between 60000 - 84000 € per year.

Location

London

Employment Type

Full time

Location Type

Hybrid

Department

Engineering

We power people’s progress.

At Preply, we’re all about creating life-changing learning experiences. We help people discover the magic of the perfect tutor, craft a personalized learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact. So far, 90,000 tutors have delivered over 20 million lessons to learners in more than 175 countries. Every Preply lesson sparks change, fuels ambition, and drives progress that matters.

About the role

We’re hiring a Staff ML & Data Engineer to own and evolve Preply’s ML platform. You will design the systems that enable our ML teams to move from research to production seamlessly — at scale, across clouds, and with minimal friction.

This role blends strategic platform architecture with deep hands‑on engineering. You’ll partner with Engineering and ML leadership to define standards, introduce new tooling, and eliminate barriers to deploying reliable, cost‑efficient, and observable ML systems.

Your mission

  • Lead the design and implementation of Preply’s ML platform architecture: from experiment tracking and artifact management to scalable model deployment
  • Drive cloud‑native solutions for distributed training and inference, including GPU‑based training environments, autoscaling, and rollout strategies
  • Own technical direction for CI/CD for ML, incorporating testing, validation, and performance checks into every deployment pipeline
  • Embed observability best practices across ML workflows: metrics, alerts, drift detection, lineage
  • Act as a multiplier across engineering: mentoring, influencing standards, and de‑risking complex technical decisions
  • Partner with ML Leads and Product teams to align platform direction with experimentation velocity, cost‑efficiency, and user impact
  • Design and lead building ML services that are modular, testable, and monitored from day one
  • Contribute to LLM platform capabilities, including RAG pipelines, latency‑optimised inference, and prompt experimentation frameworks

What we’re looking for

  • 8+ years of engineering experience in large‑scale Data/ML platforms, with proven ability to architect and scale production‑grade systems supporting dozens of ML use cases
  • Deep knowledge of cloud services and strong understanding of end‑to‑end ML workflows, including versioning, monitoring, and performance benchmarking
  • Experience with working with scientists and building enabling tools for them
  • Excellent communication and influence across cross‑functional teams; motivated by product impact. Mentoring and coaching ML engineers
  • Familiarity with LLM frameworks (LangChain, LlamaIndex), vector stores, and retrieval infrastructure

Why you’ll love it at Preply

  • An open, collaborative, dynamic and diverse culture
  • A generous monthly allowance for lessons on Preply.com, Learning & Development budget and time off for your self‑development
  • A competitive financial package with equity, leave allowance and health insurance
  • Access to free mental health support platforms
  • The opportunity to unlock the potential of learners and tutors through language learning and teaching in 175 countries (and counting)

Our Principles

  • Care to change the world – We are passionate about our work and care deeply about its impact to be life‑changing
  • We do it for learners – For both Preply and tutors, learners are why we do what we do. Every day we focus on empowering tutors to deliver an exceptional learning experience
  • Keep perfecting – To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters
  • Now is the time – In a fast‑paced world, it matters how quickly we act. Now is the time to make great things happen
  • Disciplined execution – What makes us disciplined is the excellence in our execution. We set clear goals, focus on what matters, and utilise our resources efficiently
  • Dive deep – We leverage business acumen and curiosity to investigate disparities between numbers and stories, unlocking meaningful insights to guide our decisions
  • Growth mindset – We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point. We humbly embrace feedback and learn from setbacks
  • Raise the bar – We raise our performance standards continuously, alongside each new hire and promotion. We build diverse and high‑performing teams that can make a real difference
  • Challenge, disagree and commit – We value open and candid communication, even when we don’t fully agree. We speak our minds, challenge when necessary, and fully commit to decisions once made
  • One Preply – We prioritise collaboration, inclusion, and the success of our team over personal ambitions. Together, we support and celebrate each other’s progress

Diversity, Equity, and Inclusion

Preply.com is committed to creating an inclusive environment where people of diverse backgrounds can thrive. We believe that the presence of different opinions and viewpoints is a key ingredient for our success as a multicultural Ed‑Tech company. That means that Preply will consider all applications for employment without regard to race, colour, religion, gender identity or expression, sexual orientation, national origin, disability, age or veteran status

#J-18808-Ljbffr

Staff Machine Learning Platform/Ops Engineer employer: Preply

At Preply, we pride ourselves on fostering an open and collaborative culture that values diversity and innovation. As a Staff ML & Data Engineer, you'll not only have the opportunity to shape our cutting-edge ML platform but also benefit from generous learning allowances, competitive financial packages, and a strong commitment to employee growth and well-being. Join us in making a meaningful impact in the world of language learning while working in a dynamic environment that encourages continuous improvement and teamwork.

Preply

Contact Detail:

Preply Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Staff Machine Learning Platform/Ops Engineer

Tip Number 1

Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people 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 related to ML platforms. 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 practising common technical questions and scenarios relevant to ML engineering. Mock interviews with friends or using online platforms can help you feel more confident and ready to impress.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!

We think you need these skills to ace Staff Machine Learning Platform/Ops Engineer

Machine Learning Platform Architecture
Cloud Services
Distributed Training and Inference
CI/CD for ML
Experiment Tracking
Artifact Management
Observability Best Practices

Some tips for your application 🫡

Tailor Your Application:Make sure to customise your CV and cover letter for the Staff ML & Data Engineer role. Highlight your experience with large-scale Data/ML platforms and any relevant cloud services you've worked with. We want to see how your skills align with our mission!

Showcase Your Impact:When detailing your past experiences, focus on the impact you made in previous roles. Did you improve deployment processes or mentor other engineers? We love to see how you've contributed to team success and product impact!

Be Clear and Concise:Keep your application clear and to the point. Use straightforward language to describe your technical skills and experiences. We appreciate clarity, especially when it comes to complex topics like ML workflows and cloud-native solutions.

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, we love seeing applications come directly from our site!

How to prepare for a job interview at Preply

Know Your ML Platforms

Make sure you’re well-versed in the latest ML platforms and tools. Familiarise yourself with cloud services, CI/CD processes, and observability best practices. Being able to discuss your experience with these technologies will show that you’re ready to hit the ground running.

Showcase Your Collaboration Skills

This role requires working closely with cross-functional teams. Prepare examples of how you've successfully collaborated with engineers and ML scientists in the past. Highlight your communication skills and how you’ve influenced technical decisions to drive product impact.

Demonstrate Your Problem-Solving Mindset

Be ready to discuss complex technical challenges you've faced and how you approached solving them. This could include designing scalable systems or optimising model deployment. Showing a growth mindset and your ability to learn from setbacks will resonate well with the interviewers.

Prepare for Technical Questions

Expect in-depth technical questions related to ML workflows, versioning, and performance benchmarking. Brush up on your knowledge of LLM frameworks and vector stores. Practising coding problems or system design scenarios can also help you feel more confident during the technical portion of the interview.