Pi

About us:

Pi - India’s 1st SuperMoney App, is an AI-native Fintech startup building ML platforms for financial advisory and wealth management. Founded by a former Investment Banker (IIT/IIM/ CFA®) with over a decade of experience.

We are looking for Machine Learning Engineers who are passionate about developing world-class ML platforms. You will be part of the Core Founding team that lays the foundation for a Unicorn journey. You'll join a visionary, funded startup on the ground floor and get to build it up one conversation at a time.

Qualifications:

• Overall experience of 4 to 7 years in ML
• B.Tech/BE from top-tier colleges (IIT, NIT, IIIT)

Requirements:

• Applied GenAI expertise in implementing cutting-edge LLMs and diverse generative models, specializing in transformers and GPT models.
• Demonstrated proficiency across various modalities, showcasing a dynamic skill set for innovative solutions.
• Expertise in Natural Language Processing (NLP), with a comprehensive understanding of the entire stack involved in designing, training, evaluating, and deploying machine learning models, particularly large language models.
• Deep understanding of the entire stack when it comes to designing, training, evaluating, and deploying ML models. Successfully collected a new giant dataset and played a critical role in shipping a new ML product that required custom components.
• Extensive experience in designing and building intelligent agents, leveraging AI techniques to create autonomous and adaptive systems for various applications.
• Proficient in writing distributed ML infrastructure, debugging and fixing hard-to-find bugs in ML models, and owning production-grade projects from start to finish.
• Experience with Deep learning frameworks such as PyTorch, TensorFlow. , Jax, and Keras.
• Proficient in writing GPU kernels using CUDA .
• Experience with AWS SageMaker and the AWS Machine Learning suite of tools.
• Developed novel techniques for ML model measurement and mitigation.
• Proficient in Apache Kafka for seamless data streaming, Apache Spark for large-scale batch processing, and Apache Airflow for efficient orchestration.
• Demonstrated expertise in Kubernetes-based workflows, specifically Kubeflow, for scalable and portable machine learning and data processing deployments, enhancing pipeline reliability and performance.
• Experience with MongoDB, MySQL, and Vector databases.
• Experience with analytics.
• Proficient in Kubernetes, Python, Github, Huggingface, R(for Analytics)
• Experience in mentoring and growing engineers.

Additional Benefits:

Competitive compensation along with ESOPs of a path-breaking Fintech startup