Description:

The Machine Learning Engineer role is responsible for the design, development, and implementation of machine learning solutions to serve the organization.
This 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.
Responsibilities include the development and deployment of machine learning models for localization and business workflow processes, including machine translation and quality assurance.
The engineer will maintain code quality by writing well-documented, efficient, and clean Python code following best practices.
Collaboration with cross-functional teams is essential to implement solutions based on defined designs and to support clear communication of technical progress.
The engineer will contribute to developing accurate and efficient models aligned with project requirements and take ownership of key projects from definition to delivery.
Evaluation and selection of appropriate machine-learning techniques and algorithms to solve specific problems is also a key responsibility.
The role requires a commitment to continuous learning and the ability to propose solutions and strategies to tackle business challenges.

Requirements:

A Bachelor's or Master's degree in Computer Science, Machine Learning, Mathematics, Data Science, or a similar discipline, or equivalent experience is required.
A minimum of 3 years of experience as a Machine Learning Engineer or in a similar role is essential.
A solid understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and classification techniques is necessary.
Hands-on experience with natural language processing (NLP) techniques and tools is required.
Proficiency in Python, with the ability to write clean, well-structured code following best practices, is essential.
Good communication and documentation skills are necessary to explain technical work clearly to peers and team members, especially to non-technical stakeholders.
Experience using Large Language Models in production is a plus.
Proficiency with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn is desirable.
Experience with AWS technologies, including EC2, S3, and other deployment strategies, is beneficial, with experience in SNS and Sagemaker being a plus.
Knowledge of ML management technologies and deployment techniques, such as AWS ML offerings, Docker, and GPU deployments, is advantageous.
Familiarity with data visualization tools like matplotlib, bokeh, and d3.js is preferred.
An analytical mind and business acumen are important.
The ability to collaborate in an international environment and within a distributed team is required.

The position offers the opportunity to work in a trusted global transformation partner environment, contributing to innovative language services.
Employees will have the chance to engage with a diverse range of projects and technologies, enhancing their professional growth.
The role supports continuous learning and staying updated with new techniques in machine learning.
The company promotes a collaborative work culture, allowing for effective teamwork and communication.
The position is remote, providing flexibility in work arrangements.
Employees will be part of a growing network of over 400,000 in-country linguistic resources, enhancing their exposure to global markets.