At a Glance
- Tasks: Build and maintain ML pipelines for training, evaluation, and deployment.
- Company: Join Preply, a dynamic Ed-Tech company transforming learning experiences worldwide.
- Benefits: Enjoy competitive pay, equity, health insurance, and a generous learning allowance.
- Why this job: Make a real impact by shaping AI-powered learning for students globally.
- Qualifications: 5+ years in ML systems, proficiency in Python and SQL, and cloud experience.
- Other info: Collaborative culture with opportunities for personal and professional growth.
The predicted salary is between 48000 - 72000 ÂŁ per year.
We power people's progress. At Preply, we're all about creating lifeâchanging 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 humanâled, techâenabled - 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.
As Preply scales its AIâpowered learning platform, we're looking for an experienced senior ML Platform/Ops Engineer to help productionise machine learning systems with high reliability, performance, and observability. You'll work at the intersection of ML, data engineering, and cloud infrastructure enabling fast, secure, and reproducible model development from training to deployment. You'll collaborate closely with ML Scientists, Backend Engineers, and Data Engineers to shape the foundations of our ML lifecycle.
What you'll be doing:
- Build and maintain ML pipelines for training, evaluation, and deployment using tools like Databricks, MLFlow, Airflow, DBT, Sagemaker, Tecton.
- Support AI scientists creating reproducible, containerised model training environments (onâdemand and scheduled), and manage compute at scale (e.g., spot/GPU autoscaling).
- Define and implement observability and alerting for ML systems (model drift, data quality, feature coverage, etc.).
- Design and scale data ingestion and feature transformation flows using batch (e.g., Spark/BigQuery) and streaming (Kafka or equivalent).
- Contribute to internal Python libraries and platform tooling that accelerate experimentation and deployment for all model teams.
- Ensure ML services are modular, testable, and monitored from day one.
- Exploration and productionisation of LLMâbased features (e.g., retrieval pipelines, prompt evaluation, model serving).
What we're looking for:
- Proven experience designing and deploying ML systems in production (5+ years in relevant roles).
- Proficiency in Python and SQL, and orchestration tools (Airflow, Kubeflow, Dagster, etc.).
- Experience with modern cloud platforms (preferably GCP or AWS), Kubernetes, and CI/CD workflows.
- Understanding of ML model lifecycles: training, validation, deployment, and monitoring.
- Ability to work independently with ML Scientists and mentor peers in reliability, testing, and delivery. Product impact driven.
- Exposure to LLM serving, vector databases, or GenAIâpowered product flows.
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 selfâdevelopment.
- 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!).
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 fastâpaced 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 highâperforming 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 EdâTech 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.
Senior Machine Learning Platform/Ops Engineer Location: London employer: Preply Inc.
Contact Detail:
Preply Inc. Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior Machine Learning Platform/Ops Engineer Location: London
â¨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.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML systems. This gives potential employers a taste of what you can do and sets you apart from the crowd.
â¨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to ML Ops. Mock interviews with friends or mentors can help you feel more confident and ready to impress.
â¨Tip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission at Preply.
We think you need these skills to ace Senior Machine Learning Platform/Ops Engineer Location: London
Some tips for your application đŤĄ
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with ML systems and cloud platforms. We want to see how your skills align with what we're looking for, so donât hold back on showcasing your relevant projects!
Show Your Passion: Let us know why you're excited about the role and our mission at Preply. Share any personal experiences or projects that demonstrate your enthusiasm for machine learning and education. We love seeing candidates who are genuinely passionate about what they do!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. Use clear language to describe your achievements and skills. We appreciate a well-structured application that makes it easy for us to see your qualifications at a glance.
Apply Through Our Website: We encourage you to submit your application directly through our website. This helps us streamline the process and ensures your application gets the attention it deserves. Plus, itâs super easy to do!
How to prepare for a job interview at Preply Inc.
â¨Know Your Tech Stack
Make sure youâre well-versed in the tools mentioned in the job description, like Databricks, MLFlow, and Airflow. Brush up on your Python and SQL skills, as you'll likely be asked to demonstrate your proficiency during the interview.
â¨Showcase Your Experience
Prepare specific examples from your past roles where you've successfully designed and deployed ML systems. Highlight your experience with cloud platforms like GCP or AWS, and be ready to discuss how youâve tackled challenges in production environments.
â¨Understand the ML Lifecycle
Familiarise yourself with the entire ML lifecycle, from training to deployment and monitoring. Be prepared to discuss how you ensure model reliability and performance, and how you handle issues like model drift and data quality.
â¨Emphasise Collaboration
Since the role involves working closely with ML Scientists and Engineers, be ready to talk about your collaborative experiences. Share how youâve mentored peers or contributed to team projects, showcasing your ability to work in a dynamic environment.