ML Engineer

We are a team of Machine Learning Engineers focused on turning ideas and prototypes into reliable, production-ready systems. We own the end-to-end lifecycle of ML solutions — from integration with existing services to deployment, monitoring, and continuous improvement — ensuring our models deliver stable, measurable value in real-world conditions.

Key Responsibilities

• Take ownership of the end-to-end machine learning delivery cycle, including building, testing, deploying, and supporting solution components

• Lead the design of complex ML systems from scratch, considering architectural aspects, user needs, and non-functional requirements

• Transform business goals into data science problems and define relevant proxy metrics and non-functional requirements

• Discover and verify business scenarios that can be solved with technical tools and solutions, contributing significantly to the experiment design process

• Manage issues from root cause to resolution, providing feedback to improve engineering design and prevent future issues

• Create and maintain DS-powered services in a production environment, collaborating with other teams and contributing to the backend systems and infrastructure

• Drive automation and track performance and efficiency metrics

• Mentor and onboard junior team members, supporting a culture of continuous learning and best practices

• Communicate complex technical messages clearly and concisely to diverse audiences

• Proactively identify and report potential security, risk, and control issues

• Drive continuous improvement and innovation that leads to business impact

Skills, Knowledge and Expertise

• Comprehensive experience autonomously implementing and leading ML projects, with a proven track record of successes and lessons learned

• Expert-level proficiency in classic machine learning, deep learning, and advanced mathematics

• Strong practical knowledge of MLOps instruments for managing the ML model lifecycle

• Solid software system design skills to contribute to overall architecture, and the ability to design ML systems from scratch

• In-depth experience with event systems and deployment environments, and the ability to maintain services in production

• Proficiency in Python and its frameworks for streaming, batch, and async data processing

• Common knowledge of technologies for backend integration (e.g., Golang)

• A strong grasp of concepts like Concept Drift and its impact on model performance in production

• A strong understanding of data preparation and calculations at all stages of the ML pipeline

Why join us

• Help us challenge injustice by creating fair choices for millions of people across 1100+ cities in 48 countries.

• Develop your professional skills with access to mentoring, career consulting, and learning programs.

• Collaborate with teams around the world and gain international experience through our Global Talent Exchange Program.

• Engage in company-wide challenges, awards, sports activities, employee-led social impact and volunteering projects.

• Work alongside people who take initiative, speak openly, and challenge themselves to grow.

• Improve your language skills through co-financed courses and internal speaking clubs.

Final benefits may vary depending on the location.