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Location
Hybrid (Almaty, Kazakhstan)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 21, 2026. First seen by Alion on Oct 15, 2026.

Overview
Company
Impact
Profile match
InDrive is a global mobility and urban services platform best known for its ride-hailing app, which operates on a unique peer-to-peer pricing model. Founded in Siberia in 2012 and now headquartered in the United States, the platform allows passengers and drivers to negotiate and agree upon fares directly rather than relying on automated algorithms. Beyond ride-sharing, the company has expanded its offerings across dozens of countries to include intercity transportation, freight delivery, courier services, and local task assistance.

Our AI Customer Support and Safety team is working on many areas including Computer Vision, NLP, RL etc, bringing business value to our products and improving the lives of our customers. Now we are aiming to strengthen several streams and looking for an experienced middle Machine Learning Engineer, who will help us in our journey. The primary focus for this position will be automation of the driver verification process, for which experience in computer vision is essential.

Key Responsibilities

  • Develop, deploy, and maintain machine learning models and systems
  • Conduct in-depth data analysis, preparation, and processing
  • Contribute to the design of ML systems, focusing on data-related aspects like annotation and processing
  • Follow established security guidelines and identify potential risks
  • Collaborate with peers to review and ensure designs are effective, flexible, and reusable
  • Solve issues and provide feedback for engineering design and delivery processes
  • Ensure that features are deployed according to requirements and operate without unintended side effects
  • Create and maintain comprehensive documentation for models and processes
  • Monitor and support deployed solutions to ensure they meet performance expectations
  • Actively seek out information and internal solutions to ensure reusability and adoption of common technologies

Our expectations

  • 3+ years of experience in the Field. Previous software engineering experience is preferrable
  • Strong proficiency in Python and its common data processing frameworks (e.g., for streaming, batch, and asynchronous data).
  • Strong foundational knowledge in classical machine learning, deep learning, and advanced mathematics.
  • Familiarity with MLOps principles and experience using MLOps tools for managing the ML model lifecycle.
  • Experience with backend systems and infrastructure, and a willingness to learn new technologies (like Golang) for integration purposes.
  • The ability to design solutions using common design patterns and various design tools.
  • Experience in experiment design and the ability to validate the credibility of information from various sources.
  • A solid understanding of the business value of delivered features.
  • Strong problem-solving skills, with an emphasis on using technical facts and reasoning.
  • Excellent communication and collaboration skills, including active listening and the ability to build consensus.
  • A strong drive for continuous self-development and a collaborative mindset for contributing to communities.
  • Ability to balance quality and speed depending on the case, and justify your decision
  • Ability to explain the background and consequences of your technical decisions to non-technical stakeholders, including product and business managers
  • English communication skills

Why join us

  • Help us challenge injustice by creating fair choices for millions of people across 47 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.

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