Senior Machine Learning Platform/Ops Engineer

Preply
City of London
1 week ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer (MLOps)

Senior Machine Learning Researcher | AI Hospitality Platform | London, Hybrid | Up to £200,000+ Equity & Benefits

Senior Machine Learning Researcher | AI Hospitality Platform | London, Hybrid | Up to £200,000+ Equity & Benefits

Senior Machine Learning Engineer...

Senior Machine Learning Engineer

Senior Machine Learning Engineer

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


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.