Ai Machine Learning Engineer

The Machine Learning R&D Engineer role is responsible for the design, development and implementation of machine learning solutions to serve our organization.
This includes ownership or oversight of projects from conception to deployment with appropriate AWS services, Docker, MLFlow, and others.
The role also includes responsibility for following best practices with which to optimize and measure the performance of our models and algorithms against business goals.Responsibilities:Machine learning model research and development: design, develop and deploy machine learning models for localization and business workflow processes, including machine translation and quality assurance.
Utilize appropriate metrics to evaluate model performance and iterate accordingly.Ensure code quality: Write robust, well-documented, and structured Python code.Define and design solutions to machine learning problems: Work closely with cross-functional teams to understand business requirements and design solutions that meet those needs.
Explain complex technical concepts clearly to non-technical stakeholders.Mentorship: Guide junior team members and contribute to a collaborative team environment.Success indicators of a Machine Learning R&D Engineer:Effective Model Development: success is evident when the models developed are accurate, efficient, and align with project requirements.Positive Team Collaboration: demonstrated ability to collaborate effectively with various teams and stakeholders, contributing positively to project outcomes.Continuous Learning and Improvement: a commitment to continuous learning and applying new techniques to improve existing models and processes.Clear Communication: ability to articulate findings, challenges, and insights to a range of stakeholders, ensuring understanding and appropriateness.Requirements:Excellent, in-depth understanding of machine learning concepts and methodologies, including supervised and unsupervised learning, deep learning, and classification.Hands-on experience with natural language processing (NLP) techniques and tools.Ability to write robust, production-grade code in Python.Excellent communication and documentation skills.
Able to explain complex technical concepts to non-technical stakeholders.Experience taking ownership of projects from conception to deployment.
Ability to transform business needs to solutions.Nice to have:Experience using Large Language Models in production.High proficiency with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.Hands-on experience with AWS technologies including EC2, S3, and other deployment strategies.
Experience with SNS, Sagemaker a plus.Experience with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, GPU deployments, etc.Education and Experience:BSc in Computer Science, Mathematics or similar field.Master's Degree is a plus.5+ years' experience as a Machine Learning Engineer or similar role.Benefits:National public holidays.Vacations: 3 weeks per year.Work laptop provided.About Us:Founded in 2005, tbo.
is a global organization that provides translation, talent, training, teams and testing services to a full range of clients in over 40 countries worldwide, from startups to enterprise-level companies.tbo.
aims to facilitate global communication by bridging the gap between peoples and cultures, providing simple solutions to complex problems, and outstanding service in 100+ languages.Company Culture:tbo.
fosters a culture of continuous improvement, creativity, sustainability and community, with a longstanding commitment to providing high-touch human service.Growth Opportunity:tbo.
It is ranked as one of the fifteen fastest organically growing localization companies in the world and operates 24/7, 363 days a year on a "follow the sun" format via offices in Cordoba, Ho Chi Minh City, Kyiv and Lima.Certified under five separate international quality norms.Join our growing staff and boost your career in a global organization
At tbo.
, we believe that fostering an inclusive culture and a diverse environment makes us stronger.
We are an equal opportunity employer, dedicated to creating a space where everyone can thrive and grow.
We are committed to ensuring our hiring processes are fair, transparent, and in compliance with all legal and policy requirements, promoting a workplace free from discrimination.
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