About drivebuddyAI
We're drivebuddyAI. We aim to accelerate the evolution in the future of mobility through the transformation of the Fleet Management, Insurance Ecosystem & Autonomy. We are on a mission to enable commercial fleets with an AI-powered intelligent driver & fleet safety platform, ensuring drivers’ safety, reducing high-risk-loss-making events, and improving efficiency.
If you're looking to play a part in making a positive impact in the world by advancing revolutionary work in the mobility domain, join us.
This is a role for someone who has worked on complex business problems and solved it till production level for any of the emerging verticals like retail, medical, industrial, automotive.
What you'll be doing
- Building a scalable DS & ML algorithms for profiling or personas, pattern identification using statistical modelling, machine learning techniques
- Modelling, Validating, importing, cleaning & transforming data with the purpose of extracting insights for the decision making process
- Data gathering, analysis & report generations
- Use Python or equivalent statistical/data analysis tools and write production quality code
- Manage ML lifecycle including experimentation, reproducibility and deployment
- Work with data storage like SQL & NoSQL DBs
- Work with AWS on deployment & MLOps
- Design and Develop feedback system to improve the overall accuracy & precision
- Build & Implement performance parameters aligned to the problem statement
- Collaborate with others, from hardworking team members within your group, through smart technologists in cross-functional teams like Data Science, Embedded & Cloud and responsible leaders across DBAI.
- Building up strong relationships with people in the organization, meaningfully collaborating, and building trust.
- Have a vision and identify strategically important problems, inefficiencies, or opportunities for meaningful improvements.
- Raise the bar on engineering excellence by improving standard practices, producing the best in a class of code, documentation, testing, and monitoring.
What you must have
- Ability to execute a project with above mentioned process/activities with the team
- 3-5 years of experience in building, shipping, debugging, and operating full-stack ML application in a production environment.
- Experience with classical ML algorithms
- Experience with mathematical models for data patterns & profiling
- Hands on experience with OpenCV
- Experience with underline mathematics of ML models
- Must be well-versed with model debugging techniques
- Familiarity with working on multi-GPU rigs & cloud GPUs with Linux OS