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Prodigal

Senior Machine Learning Engineer

Reposted 23 Days Ago
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In-Office
Mumbai, Maharashtra
Senior level
In-Office
Mumbai, Maharashtra
Senior level
The Senior Machine Learning Engineer will design, develop, and deploy ML and Generative AI solutions, ensuring high performance and reliability, while leading collaboration efforts with cross-functional teams.
The summary above was generated by AI

At Prodigal, we’re reshaping the future of consumer finance. Founded in 2018 by IITB alumni, our journey began with one bold mission: to eradicate the inefficiencies and confusion that have plagued the lending and collections industry for decades.

Today, we stand at the forefront of a seismic shift in the industry, pioneering the concept of consumer finance intelligence. Powered by our cutting-edge platform, Prodigal’s Intelligence Engine, we’re creating the next-generation agentic workforce for consumer finance—one that empowers companies to achieve unprecedented levels of operational excellence.

With over half a billion consumer finance interactions processed and a growing impact on more than 100 leading companies across North America, we’ve established ourselves as the go-to partner for organizations that demand more from their AI solutions. Our unparalleled experience, coupled with our trusted customer relationships, uniquely positions us to build generative AI solutions that will revolutionize the future of consumer finance.

At Prodigal, we are driven by a singular, unrelenting purpose: to transform how consumer finance companies engage with their customers and, in turn, drive successful outcomes for all. 

We are looking for a passionate and seasoned Senior Machine Learning (ML) Engineer to spearhead the design, development, and deployment of cutting-edge Machine Learning and Generative AI solutions towards Prodigal’s vision of building the Intelligence Layer for Consumer Finance. 

Responsibilities:
  • ML Algorithm Development: Design and implement advanced ML algorithms leveraging traditional Machine Learning techniques and the modern NLP stack, including Large Language Models (LLMs)
  • Data Engineering & Software Development: Architect and implement data pipelines for ML model training. Lead scalable software systems development to deploy ML models into production systems, ensuring high performance and reliability.
  • Research & Innovation: Stay updated on ML research and the ever-changing Gen AI landscape, identifying opportunities for innovation.
  • Collaboration & Leadership: Effectively collaborate with cross-functional teams to deliver high-quality solutions on time. Guide team members in contributing to ML design discussions for new projects.
Requirements:
  • Extensive experience (5-8 years) in software development, with a focus on machine learning and data science in a tech company. 
  • Proven track record of delivering high-quality ML products in a fast-paced, agile environment.
  • Deep understanding of machine learning algorithms with hands-on experience in developing and deploying machine learning models at scale.
  • Strong coding skills in Python. Familiarity with machine learning libraries such as PyTorch and sci-kit-learn. Experience with data manipulation and analysis tools like Pandas and Spark.
  • Strong communication and leadership skills, with the ability to effectively collaborate with cross-functional teams and mentor junior engineers.
Preferred Qualifications:
  • Experience training and using Large Language Models (BERT, LLAMA, GPT etc) with a passion for applying Generative AI solutions in production environments.
  • Experience with cloud services (AWS) and building scalable, distributed systems.

Mode Of Work - In-Office


Job Benefits 
  • World-class team - You'll get the chance to learn from (and teach) some of the brightest and most skilled people you'll ever meet. Our team members have been part of BCG, Deloitte, EY, Blackstone, Meta, Amazon and are IIT, IIM, BITS alumnus.
  • Continuous education - As relentless seekers of knowledge, we sponsor and support any training materials, books, courses, and exam fees for upskilling yourself in areas related to your role - but that's not where it ends. If you make a good case for some extra learning, we're delighted to foot the tab.
  • Food at the office – Meals are on us. We won't let your stomach grumble while you hustle.
  • Health insurance - Health always comes first. The health of your family is as important to us, as it is to you. We offer insurance coverage for both you and your family.
  • Flexible schedule - We're not a "clock in, clock out" company. Morning person? Start work while the world's still sleeping. Night owl? Ramp things up while others are winding down. You're fully trusted to create the right conditions for your own personal peak productivity. We only ask that you be available to your teammates for seamless collaboration.
  • Generous leave policy - Take all the time you need to recharge your batteries - no cap on vacation allowance here. Because a rested, relaxed, and refreshed mind is a happy and effective mind.
  • Recreation & team activities – We regularly indulge in friendly football, table tennis, cooking sessions and challenge each other to do those extra push ups or chug that 4th drink (of course that’s Nimbu Pani)

Meet Sangram - (Cofounder and CTO) and hear his vision for Prodigal below (01:38)

                                         

From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents one of the biggest industries in the US.

To learn more about us - please visit the following:

Our Story - https://www.prodigaltech.com/our-story

What shapes our thinking - https://link.prodigaltech.com/our-thesis

Our website - https://www.prodigaltech.com/ 

Top Skills

AWS
Pandas
Python
PyTorch
Sci-Kit Learn
Spark

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