Machine Learning Engineer

Ring is a “Made in India” online Instant Credit Platform operated by OnEMi Technology Solutions Pvt Ltd with an aim to provide their coveted “PaywithRing Limit” product to their customers across India.

Ring is conceptualized to provide an instant credit facility to its customers. It also allows the customer to walk in at any merchant store that accepts payments from UPI apps like BHIM, PhonePe, Paytm, Freecharge, Mobikwik, Axis Pay, Jio Pay, etc. This revolutionary product aptly named “PaywithRing Limit” enables the customer to buy their favorite products at any merchant store of their choice using the PaywithRing Credit Line to be repaid as per the stipulated time. Being 100% digital, Ring makes it easier for customers to scan QR codes at their preferred merchant stores.

Ring is also a Great Place to Work certified company.

Job Description:

As a Machine Learning Engineer(GenAI), you will work on developing ML solutions that will be used to power up new products and used by various teams as part of the key initiatives in technology and data management domains and will contribute to firmwide impact.

Must-Have:

Proficiency in at least one of the major programming scripting languages used in Gen AI

Experience with Machine learning models and NLP techniques like BERT, Transformers, Deep learning and tuning Large Language Models

Experience working with RAG technologies and LLM frameworks (Langchain and LLamaIndex), LLM model registries (Hugging Face), LLM APIs, embedding models, and vector databases (Pinecone/Chroma/FAISS)

Implementation exposure to LLM agents like LangChain

Hands-on exposure to integrating atleast one of the popular LLMs(Open AI GPT, PaLM 2, Dolly, Claude 2, Cohere etc.) using API endpoints.

Advanced knowledge of building API based scalable solutions such as Django/Flask/FastAPI, etc.

Knowledge of Python libraries like Pandas, Scikit-Learn, Numpy, NLTK, Spacy and Scipy is required

Experience with machine learning libraries and services like TensorFlow, PyTorch, or Amazon SageMaker.

Experience building scalable data models and performing complex relational database queries using SQL (Snowflake, MySQL, PostGres), etc.

Build and maintain data pipelines and infrastructure to support AI Solutions

Hands-on exposure to using cloud services (Azure/GCP/AWS)

Solid knowledge of software engineering best practices, including version control systems (e.g., Git), code reviews, and testing methodologies.

Good problem-solving skills and excellent verbal and written communication skills