Company Overview

Bridgenext is a Global consulting company that provides technology-empowered business solutions for world-class organizations. Our Global Workforce of over 800 consultants provides best-in-class services to our clients to realize their digital transformation journey. Our clients span the emerging, mid-market and enterprise space. With multiple offices worldwide, we are uniquely positioned to deliver digital solutions to our clients leveraging Microsoft, Java, and Open Source with a focus on Mobility, Cloud, Data Engineering, and Intelligent Automation. Bridgenext’s singular mission is to create “Clients for Life” - long-term relationships that deliver rapid, meaningful, and lasting business value.

At Bridgenext, we have a unique blend of Corporate and Entrepreneurial cultures. This is where you would have an opportunity to drive business value for clients while you innovate and continue to grow and have fun while doing it. You would work with team members who are vibrant, smart and passionate and they bring their passion to all that they do – whether it’s learning, giving back to our communities or always going the extra mile for our client.

Position Description

We are looking for a Machine Learning Engineer with hands-on experience in machine learning models who will work on the internal and customer-based projects for Bridgenext. We are looking for someone who cares about the quality of the code and who is passionate about providing the best solution to meet the client’s needs and anticipates their future needs based on an understanding of the market.

Must Have Skills :

• 2-4 years of overall experience
• 2+ years of experience with structured data using popular machine learning libraries and frameworks.
• High level of experience with Python
• Technology expertise of solutioning in PySpark, LightGBM, Kubeflow, Jupyter notebook, machine learning Ops, Model version documentation, SQL, tableau, Pandas, Git / Gitlab / Github.
• Good to have AWS Cloud experience, Hadoop, Hive.
• Should be able to maintain the machine learning model in a production environment, ensuring its reliability and optimal performance.
• Skill in analyzing model performance metrics, identifying areas for improvement, and implementing strategies to enhance overall model effectiveness.
• Should be able to identify and rectify bugs in the machine learning model, implementing timely and effective solutions.

Professional Skills :