At a Glance
- Tasks: Build and maintain ML pipelines, ensuring high reliability and performance.
- 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 the future of AI-powered education.
- Qualifications: 5+ years in ML systems, proficiency in Python, SQL, and cloud platforms.
- Other info: Collaborative culture focused on growth, diversity, and continuous improvement.
The predicted salary is between 48000 - 72000 £ per year.
Senior Machine Learning Platform/Ops Engineer
Apply for the Senior Machine Learning Platform/Ops Engineer role at Preply.
As Preply scales its AI-powered learning platform, we’re looking for an experienced Senior ML Platform/Ops Engineer to help productionize 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 scientist creating reproducible, containerized model training environments (on-demand 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 productionization of LLM-based 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
- Strong DevOps practices: Git, IaC (Terraform), logging/observability, containerization (Docker/K8s)
- 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 GenAI-powered 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 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 utilize 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 prioritize collaboration, inclusion, and the success of our team over personal ambitions. Together, we support and celebrate each other\’s progress.
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, color, religion, gender identity or expression, sexual orientation, national origin, disability, age or veteran status.
Seniority Level
Mid-Senior level
Employment Type
Full-time
Job Function
Engineering and Information Technology
Industries
Technology, Information and Internet
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Senior Machine Learning Platform/Ops Engineer employer: Preply
Contact Detail:
Preply Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior 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 or GitHub repository showcasing your projects and contributions. This is a great way to demonstrate your expertise in ML systems and cloud platforms to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to ML and DevOps. Practice explaining your past projects and how they align with the role at Preply.
✨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, it shows you’re genuinely interested in joining the Preply team.
We think you need these skills to ace Senior Machine Learning Platform/Ops Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Senior ML Platform/Ops Engineer role. Highlight your experience with ML systems, cloud platforms, and any relevant tools like Databricks or Airflow. We want to see how your skills align with what we’re looking for!
Showcase Your Projects: Don’t just list your skills; show us what you’ve done! Include specific projects where you’ve designed or deployed ML systems. This gives us a clear picture of your hands-on experience and how you can contribute to our team.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language and avoid jargon unless it’s relevant. We appreciate a well-structured application that gets straight to the point without fluff!
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, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at Preply
✨Know Your ML Tools
Familiarise yourself with the specific tools mentioned in the job description, like Databricks, MLFlow, and Airflow. Be ready to discuss your experience with these tools and how you've used them to build and maintain ML pipelines.
✨Showcase Your Collaboration Skills
Since the role involves working closely with ML Scientists and Backend Engineers, prepare examples of past collaborations. Highlight how you’ve contributed to team projects and how you can mentor peers in reliability and testing.
✨Demonstrate Your DevOps Knowledge
Brush up on your understanding of DevOps practices, especially around CI/CD workflows and containerization with Docker and Kubernetes. Be prepared to explain how you’ve implemented these practices in previous roles.
✨Prepare for Technical Questions
Expect technical questions related to ML model lifecycles and observability. Practice explaining concepts like model drift and data quality, and be ready to discuss how you would define and implement alerting for ML systems.