Senior Machine Learning Engineer

About the Company : Saarthee is global analytics consulting firm unlike any other, where our passion for helping others fuels our approach and our products and solutions. We are a one-stop shop for all things data and analytics. Unlike other analytics consulting firms that are technology or platform specific, Saarthee’s holistic and tool agnostic approach along with ability delivery strategic actionable insights is unique in the marketplace. Our Analytics Value Chain framework meets our customers where they are in their data journey. Our diverse and global team of skilled data engineers, data analysts, and data scientists work with one objective in mind : Our Customers’ Success. At Saarthee, we are passionate about guiding organizations towards insights-fueled success. That’s why we call ourselves Saarthee–inspired by the Sanskrit ‘Saarthi’, which means charioteer, trusted guide, or companion. Co-founded in 2015 by Mrinal Prasad and Shikha Miglani, Saarthee already encompasses all the components of Data Analytics consulting. Saarthee is based out of Philadelphia, USA with office in UK and India.

About the Role : The 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 :

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

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

Pay range and compensation package : Best in the Industry.