Description:

The Machine Learning R&D Engineer role is responsible for the design, development, and implementation of machine learning solutions to serve the organization.
This position includes ownership or oversight of projects from conception to deployment using appropriate AWS services, Docker, MLFlow, and others.
The role involves following best practices to optimize and measure the performance of models and algorithms against business goals.
Key tasks include designing, developing, and deploying machine learning models for localization and business workflow processes, including machine translation and quality assurance.
The engineer will utilize appropriate metrics to evaluate model performance and iterate accordingly.
The role requires writing robust, well-documented, and structured Python code to ensure code quality.
The engineer will work closely with cross-functional teams to understand business requirements and design solutions that meet those needs.
Mentorship of junior team members and contributing to a collaborative team environment is also a responsibility.
Success indicators include effective model development, positive team collaboration, continuous learning and improvement, and clear communication.

Requirements:

A deep understanding of machine learning concepts and methodologies, including supervised and unsupervised learning, deep learning, and classification is essential.
Hands-on experience with natural language processing (NLP) techniques and tools is required.
The ability to write robust, production-grade code in Python is necessary.
Excellent communication and documentation skills are essential, with the ability to explain complex technical concepts to non-technical stakeholders.
Experience in taking ownership of projects from conception to deployment and transforming business needs into solutions is required.
It is preferred to have experience using Large Language Models in production.
High proficiency with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn is a plus.
Hands-on experience with AWS technologies including EC2, S3, and other deployment strategies is preferred, with experience in SNS and Sagemaker being a plus.
Familiarity with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, and GPU deployments, is desirable.
A BS in Computer Science, Mathematics, or a similar field is required, while a Master’s Degree is a plus.
A minimum of 5 years of experience as a Machine Learning Engineer or in a similar role is required.

The position offers the opportunity to work in a trusted global transformation partner environment, contributing to the acceleration of global business journeys.
Employees will have the chance to engage with a diverse range of projects and technologies, enhancing their professional growth.
The role promotes a collaborative team environment, allowing for mentorship and knowledge sharing among team members.
There is a commitment to continuous learning and improvement, providing opportunities to apply new techniques and improve existing models and processes.
The position supports remote work flexibility, allowing for a better work-life balance.