Research Engineer Applied AIML

As a Research Engineer you will be responsible for building and evolving innovative ML & DL based solutions. You are expected to have in-depth knowledge and acumen to understand the on-going research and harness it to develop products that are ready for the market.

In this role you will get a chance to work on some of the most challenging and interesting products that have a significant impact on revenue and user experience.

• At least an undergraduate degree in Machine Learning Computer Science Applied Mathematics from Tier-1 college.
• 2 years of experience at cutting edge organizations or startups 1 years for MS Research PhD Candidates.
• Code develop design and architect features. We expect you to own modules and take pride in the work products you ship.
• Awareness about the State of the Art techniques in Machine Learning & AI space.
• Proactive attitude curiosity and persistence to go the extra mile.
• Demonstrated ability to operate within intricate technical frameworks to accelerate research outcomes. Your focus is not only on conducting theoretical research but on the practical productionization of models to serve millions of users.

Qualifications :

• Establish a robust theoretical foundation in machine learning encompassing predictive modeling statistical analysis and advanced optimization methodologies.
• Leverage practical expertise to develop and deploy reinforcement learning solutions for complex problem sets.
• Demonstrate advanced Python proficiency ensuring high-quality software design and efficient algorithm implementation.
• Synthesize academic research into actionable production-ready technical implementations.
• Engineer and maintain high-concurrency performance-oriented machine learning services.
• Apply core linear algebra concepts and optimization heuristics specifically tailored for ML model efficiency.
• Exhibit specialized expertise in deep learning frameworks to build scalable neural architectures.
• Operationalize the ML lifecycle by implementing MLOps pipelines and automation tooling.
• Optimize model performance on edge or resource-constrained environments using parameter quantization and pruning techniques.
• Efficiently manage and process large-scale datasets within distributed computing environments.
• Maintain technical proficiency with state-of-the-art transformer architectures and Large Language Models (LLMs).
• Prior experience applying ML and optimization strategies within the fintech domain is highly advantageous.
• A track record of peer-reviewed publications in premier conferences (e.g. NeurIPS ICLR ACL) is strongly preferred.
• Active engagement with the open-source community and contributions to relevant projects are highly valued

Additional Information :

Candidates are responsible for safeguarding sensitive company data against unauthorized access use or disclosure and for reporting any suspected security incidents in line with the organizations ISMS (Information Security Management System) policies and procedures

Remote Work :

No

Employment Type :

Full-time