The Role
Design, build, deploy, monitor, and maintain production-ready ML systems end-to-end. Perform data analysis, annotation, and processing; apply ML algorithms; use MLOps practices; ensure reusable, extensible designs; document solutions; implement monitoring and support; troubleshoot engineering and delivery issues; and collaborate with cross-functional teams to deliver business value.
Summary Generated by Built In
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
- Build and deploy machine learning solutions from end to end, contributing to the full ML delivery cycle
- Conduct data analysis, annotation, and processing as a key part of the ML system design
- Design solutions using common patterns and tools, and propose alternative approaches when needed
- Ensure solutions meet design standards and are reusable, flexible, and extensible through peer reviews
- Deploy features and ensure they work as intended while preventing unintended side effects
- Document technical solutions and ensure all necessary monitoring and support tools are in place
- Solve issues in the engineering design and delivery process and ensure the solution meets key performance indicators and non-functional requirements
- Collaborate with team members, contribute to a community of practice, and promote the reuse of common approaches and technologies
Skills, Knowledge and Expertise
- Proficiency in Python and its frameworks for streaming, batch, and asynchronous data processing
- Solid experience with classic machine learning techniques and algorithms
- Experience using MLOps tools and practices to manage the ML model lifecycle
- Familiarity with technologies like Golang for backend system and infrastructure integration
- Ability to conduct thorough data analysis and preparation
- Strong problem-solving skills with a focus on engineering principles and data-driven reasoning
- Excellent communication and collaboration skills, with an ability to seek and validate information from various sources
- A solid understanding of business value and how it connects to delivering features
- A proactive approach to self-development and learning new skills and best practices
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.
About
inDrive is a global tech company on a mission to challenge injustice. We started in 2012 in the coldest city on Earth, when a group of friends created a way for people to agree on fair ride prices. That idea grew into one of the world’s top ride-hailing apps, now with 360M installs across 48 countries.Today, we offer more than rides: from freight and delivery to intercity travel and financial services, all designed to put people first. Our goal is to positively impact 1 billion lives by 2030. Through inVision, our non-profit arm, we support education, entrepreneurship, and equality in underserved communities.Ready to ignite your inner drive?
Skills Required
- Proficiency in Python and frameworks for streaming, batch, and asynchronous data processing
- Solid experience with classic machine learning techniques and algorithms
- Experience using MLOps tools and practices to manage the ML model lifecycle
- Familiarity with Golang for backend system and infrastructure integration
- Ability to conduct thorough data analysis and preparation
- Designing reusable, flexible, and extensible ML solutions and participating in peer reviews
- Deploy features, ensure correct behavior, and prevent unintended side effects
- Document technical solutions and set up monitoring and support tools
- Strong problem-solving skills with engineering principles and data-driven reasoning
- Excellent communication and collaboration skills
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The Company
What We Do
inDrive is a global IT and transportation platform inDrive is one of the world’s fastest growing online ride-hailing services. Its services are available in over 749 cities in 46 countries throughout the world. The Company’s app has been downloaded over 150 million times. inDrive offers other services, including intercity transportation, freight and cargo services, as well as delivery services in different markets of operations. inDrive is based in Mountain View, California, and operates regional hubs in the Americas, Asia, the Middle East, Africa and the countries of the CIS, and employs over 2,000 people. In early 2021, inDrive achieved unicorn status after closing a $140m investment round with Insight Partners, General Catalyst, and Bond Capital, which valued the company at $1.23 billion.
