Lead Data Scientist

Lead ML Engineer

Job Summary

We are seeking a Lead ML Engineer to significantly contribute to scaling Machine Learning and Artificial Intelligence efforts at Paisabazaar. This role involves working with a team that develops models powering Paisabazaar's products focused on Speech, NLP, Computer Vision, and Generative AI. Key problem areas include Automated Speech Recognition (ASR) of Hinglish customer-agent audio conversations for critical business insights, building Gen AI chatbots on rich knowledge bases, and leveraging document intelligence for intelligent spend analytics to power the chat layer.

Key Skills & Technologies:

• Data Science
• Python
• Azure/GCP/AWS (Cloud Platforms)
• Apache Spark
• Machine Learning (ML)
• NLP
• Speech Recognition
• Generative AI

About the Role

This is a role for highly technical machine learning professionals who combine outstanding oral and written communication skills with the ability to code up prototypes and productionalize solutions using a wide range of tools, algorithms, and languages. Most importantly, candidates must demonstrate the ability to autonomously plan and organize their work assignments based on high-level team goals.

Key Responsibilities

• Develop machine learning models that positively impact the business.
• Collaborate with partners across the company, including operations, product, and engineering.
• Utilize research results to shape company strategy.
• Help build a foundational set of tools and practices used by quantitative staff across the company.

Requirements

• Strong background in classical machine learning and machine learning deployments, preferably with 8+ years of experience.
• In-depth knowledge of deep learning, specializing in any of the following: Speech, NLP, Computer Vision, and Generative AI.
• Hands-on experience in PyTorch, Python, cloud platforms (AWS/Azure/GCP), and Big Data platforms to manipulate large-scale structured and unstructured datasets.
• Experience with GPU computing is a plus.
• Expert-level experience with a wide range of quantitative methods that can be applied to business problems.
• Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.
• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling.