The Role
Develop, deploy, maintain, and monitor machine learning systems, with a primary focus on computer vision automation for driver verification. Responsibilities include data analysis and preparation, annotation and processing design, MLOps lifecycle management, backend integration, experiment validation, system documentation, security risk identification, and cross-functional collaboration.
Summary Generated by Built In
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.
About
inDrive is a global tech company on a mission to challenge injustice through fair choices. 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 400M installs across 47 countries.Today, we offer more than rides: from freight and delivery to intercity travel and financial services, all designed to put people first. We are committed to having a positive impact on people’s lives both through our core business, which supports local communities via a fair pricing model; and through the work of our impact programs. Ready to ignite your inner drive?
Skills Required
- 3+ years of professional experience in the field
- Previous software engineering experience
- Strong proficiency in Python
- Experience with common data processing frameworks for streaming, batch, and asynchronous data
- Foundational knowledge of classical machine learning, deep learning, and advanced mathematics
- Familiarity with MLOps principles and tools for managing the machine learning model lifecycle
- Experience with backend systems and infrastructure
- Ability to learn technologies such as Golang for integration purposes
- Ability to design solutions using common design patterns and design tools
- Experience in experiment design and validating information credibility
- Strong problem-solving, communication, collaboration, and consensus-building skills
- English communication 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.
