Saarthee - Machine Learning Engineer - NLP/Deep Learning

About the Role :

The MLE/SMLE is tasked with enhancing interactions across user gaming experiences and systems.

This involves designing, coding, training, documenting, deploying, and evaluating large-scale machine learning systems in a cost-effective manner.

We seek individuals capable of creating exceptional products and experiences for millions of users within an agile environment, collaborating seamlessly with other teams.

Moreover, you'll have the opportunity to immerse yourself in cutting-edge ML technologies, tools, and processes, contributing to the advancement of our technical objectives and architectural initiatives.

Responsibilities :

- Develop, implement, and optimize machine learning models for various applications, including predictive safety, content personalization, search, virtual assistant, time series forecasting, and clustering.

- Utilize a wide array of state-of-the-art machine learning and deep learning technologies to address diverse machine learning problems such as multilingual text classification, language modelling, and multi-modal learning.

- Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.

- Conduct thorough exploratory data analysis to uncover patterns, trends, and valuable insights.

- Deploy machine learning models into production environments using AWS services and implement scalable and efficient solutions for real-time and batch predictions.

Qualifications :

- Bachelors degree in computer science, Engineering, Statistics, or a related field.

- 5+ years of working experience in at least one of the advanced machine learning areas including computer graphics, reinforcement learning, recommendation system, and natural language processing.

- 5+ years of Team Leading or Team Management experience is must.

- Proficiency in the Python programming language and experience with PyTorch, TensorFlow, or similar frameworks.

- Experience in designing and implementing machine learning-based solutions that ideally include online safety, voice-activated conversational systems, recommender systems, search engines, personalization, time series forecasting, and A/B testing.

- Strong machine learning, statistical and analytical skills.

Required Skills : Python, Statistics, Analytics, Machine Learning, ML Algorithm, Deep Learning, NLP, LLM, ML Ops

Preferred Skills : ML Load Balance Testing, Docker, Kubernetes, AWS.