Senior Machine Learning Engineer

Job Summary

Paisabazaar is seeking a Lead ML Engineer to scale Machine Learning and Artificial Intelligence efforts. This role involves developing models for products focused on Speech, NLP, Computer Vision, and Generative AI. Key skills for this role include Data Science, Python, Azure/GCP/AWS, Apache Spark, Machine Learning (ML), NLP, Speech Recognition, and Generative AI.

About the Role

You will be part of a team developing models that power Paisabazaar's products. Specific problems include:

• Automated Speech Recognition (ASR) of Hinglish customer-agent audio conversations and generating critical insights for business.
• Building gen AI chatbots on top of rich knowledge bases.
• Leveraging document intelligence for intelligent spend analytics that further power the chat layer of Paisabazaar.

This highly technical machine learning role requires outstanding oral and written communication skills, the ability to code up prototypes, and productionalize solutions using a large range of tools, algorithms, and languages. Most importantly, you will need the ability to autonomously plan and organize your work assignments based on high-level team goals.

Key Responsibilities

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

Requirements

• Strong background in classical machine learning and machine learning deployments is a must, preferably with 8+ years of experience.
• Knowledge of deep learning, specializing in any of the following: Speech, NLP, Computer Vision, and Generative AI.
• Hands-on experience in PyTorch, Python, cloud (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.