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Staff Machine Learning Ops Engineer

Pay
Pay not listed
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering — team source
Department: Engineering
From the employer’s posting

What you’ll work on

Full posting
  • Define the technical vision and roadmap for the ML platform

  • Lead architecture across the full ML lifecycle, from experimentation to governance

  • Design cloud-native infrastructure for distributed training and inference

  • Set technical direction for CI/CD for ML and observability standards

  • Build LLM Gateway services and GenAI evaluation and serving infrastructure

From the employer’s posting
Define the technical vision and roadmap for Preply’s ML platform
Lead the architecture of platform capabilities across the full ML lifecycle
Design cloud-native infrastructure for distributed training and inference
Set the technical direction for CI/CD for ML
building LLM Gateway services, vector retrieval infrastructure, prompt experimentation, evaluation frameworks
Apply at Preply

Posting record

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Open 4 monthsWe first saw this posting 141 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 25, 2026141 days ago
Recorded sightings
250
Last seen by us
Nov 14, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 141

Up longer than most. Similar jobs usually come down between day 8 and day 76.

Well past Preply’s usual: its jobs come down by about day 64.

From 5,460 similar postings that came down, and 21 of Preply’s. Coming down is not always a hire.

Preply is hiring

29 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • AWS
  • GCP
  • Kubernetes
Where the posting names them
- Deep understanding of cloud-native architecture and end-to-end ML workflows, including experimentation, feature management, model versioning, training, deployment, monitoring, performance benchmarking, and lifecycle management. - Strong hands-on experience with cloud platforms such as GCP or AWS, Kubernetes, distributed compute, CI/CD, observability, and infrastructure-as-code practices. - Experience building enabling tools and platform capabilities for Applied Scientists, Data Scientists, and engineering teams.

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

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Has Preply posted this job before?

Yes. We’ve followed 2 other Staff Machine Learning Ops Engineer jobs there since June 2026. All 2 are still up.

  1. BarcelonaStill up after 165 days, first seen Jun 2
  2. LondonStill up after 142 days, first seen Jun 25
  3. This jobUp 142 days so far, first seen Jun 25

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 612, the most 1,081, and the latest week had 1,068.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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 personalised learning journey, and stay motivated to keep growing. Our approach is human-led, tech-enabled - and it’s creating real impact.

We’ve just reached unicorn status with a $150M Series D, accelerating our vision to transform education through human-led, AI-enhanced learning. Today, 100,000+ tutors teach 90+ languages to learners in 180 countries - and we’re only getting started. As a category-defining company, we’re shaping what the future of learning looks like at global scale.

Every Preply lesson sparks change, fuels ambition, and drives progress that matters. Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.

Meet the team!

Preply is scaling an AI-powered learning platform used by millions of learners and tutors worldwide. As ML and GenAI become increasingly central to our product, marketplace, and operational systems, we’re looking for a Staff ML Ops Engineer to define and evolve the platform that enables machine learning at company scale.

This is a senior technical leadership role for an engineer who can combine deep hands-on expertise with platform vision. You will help define the current and future direction of Preply’s ML platform, set technical standards, and design the systems that allow ML teams to move from research to production quickly, safely, and cost-efficiently.

You’ll partner closely with Applied Science, Data, Product, and Engineering leadership to build a scalable, secure, and observable ML platform that powers multiple business lines. Your impact will come not only from the systems you design, but from the standards you set, the engineers you mentor, and the technical decisions you help de-risk across the organization.

Why is this role important:

Preply’s next stage of growth depends on making AI a scalable company-wide capability, not a collection of isolated models and experiments. This role will define how ML systems are built, deployed, monitored, and improved across the company.

You’ll shape the platform that powers personalized learning, smarter experiences for tutors and learners, marketplace intelligence, content generation, automation, and future GenAI products. The goal is to make it dramatically easier for teams to turn ML ideas into reliable, secure, cost-efficient product experiences at a global scale.

What you’ll be doing:

  • Define the technical vision and roadmap for Preply’s ML platform, ensuring it can support growing ML and GenAI adoption across multiple teams, products, and business lines.

  • Lead the architecture of platform capabilities across the full ML lifecycle: experimentation, feature engineering, artifact management, training, deployment, monitoring, retraining, and governance.

  • Design cloud-native infrastructure for distributed training and inference, including GPU-based environments, autoscaling, workload isolation, rollout strategies, and cost optimization.

  • Set the technical direction for CI/CD for ML, embedding testing, validation, security, performance checks, and release confidence into deployment pipelines.

  • Establish observability standards for ML systems, including model metrics, service health, alerts, drift detection, data quality, lineage, and business-impact monitoring.

  • Lead the evolution of Preply’s GenAI and LLM platform capabilities, including building LLM Gateway services, vector retrieval infrastructure, prompt experimentation, evaluation frameworks, latency-optimized inference, and reliable model-serving patterns.

  • Partner with Applied Science and Data leads, Product leaders, and Engineering teams to align platform investments with experimentation velocity, cost efficiency, operational reliability, and user impact.

  • Design platform abstractions, internal libraries, templates, and self-service tooling that help ML Scientists and engineers move faster without compromising reliability or security.

  • Act as a technical multiplier across engineering by mentoring senior engineers, influencing architecture, raising standards, and guiding teams through complex platform decisions.

  • Identify and eliminate bottlenecks in the path from ML research to production, making the platform easier, safer, and more efficient for all ML-powered product development.

What you need to succeed:

  • 9+ years of engineering experience, with significant depth in large-scale ML, data, infrastructure, or platform systems.

  • Proven ability to architect and scale production-grade ML platforms that support many teams, workflows, and ML use cases.

  • Deep understanding of cloud-native architecture and end-to-end ML workflows, including experimentation, feature management, model versioning, training, deployment, monitoring, performance benchmarking, and lifecycle management.

  • Strong hands-on experience with cloud platforms such as GCP or AWS, Kubernetes, distributed compute, CI/CD, observability, and infrastructure-as-code practices.

  • Experience building enabling tools and platform capabilities for Applied Scientists, Data Scientists, and engineering teams.

  • Strong technical judgment and the ability to make pragmatic architecture decisions across reliability, scalability, security, cost, and developer experience.

  • Excellent communication and influence skills, with experience aligning cross-functional stakeholders and translating platform strategy into execution.

  • Demonstrated ability to mentor engineers, raise engineering standards, and multiply the impact of teams around you.

  • Product-impact mindset: you care about building platform capabilities that accelerate experimentation, improve user experiences, and unlock measurable business value.

  • Familiarity with LLM frameworks and GenAI infrastructure, such as LangChain, LlamaIndex, vector stores, retrieval systems, prompt evaluation, model serving, or LLM observability.

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!)

#LI-AG1

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.

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, color, religion, gender identity or expression, sexual orientation, national origin, disability, age or veteran status.

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Kyiv, Ukraine

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