Responsibilities

• Building scalable DS and ML algorithms for profiling or personas, pattern identification using statistical modeling, and machine learning techniques.
• Modeling, Validating, importing, cleaning, and transforming data to extract insights for the decision-making process.
• Data gathering, analysis, and report generation.
• 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 and NoSQL DBs.
• Work with AWS on deployment and MLOps.
• Design and Develop a feedback system to improve the overall accuracy and precision.
• Build and Implement performance parameters aligned to the problem statement.
• Collaborate with others, from hardworking team members within your group to smart technologists in cross-functional teams like Data Science, Embedded, and 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 methodologies, producing the best in a class of code, documentation, testing, and monitoring.
  
  

Requirements

• Ability to execute a project with the above-mentioned process/activities with the team.
• 2+ years of experience in building, shipping, debugging, and operating full-stack ML applications in a production environment.
• Experience with classical ML algorithms.
• Experience with mathematical models for data patterns and profiling.
• Hands-on experience with OpenCV.
• Experience with the underlying mathematics of ML models.
• Must be well-versed with model debugging techniques.
• Familiarity with working on multi-GPU rigs and cloud GPUs with Linux OX.
  
  

This job was posted by Harshita Arora from Roadzen.