AI Machine Learning R&D Engineer

As a trusted global transformation partner, Welocalize accelerates the global business journey by enabling brands and companies to reach, engage, and grow international audiences. Welocalize delivers multilingual content transformation services in translation, localization, and adaptation for over 250 languages with a growing network of over 400,000 in-country linguistic resources. Driving innovation in language services, Welocalize delivers high-quality training data transformation solutions for NLP-enabled machine learning by blending technology and human intelligence to collect, annotate, and evaluate all content types. Our team works across locations in North America, Europe, and Asia serving our global clients in the markets that matter to them.

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and / or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

MAIN PURPOSE OF JOB

The AI Machine Learning Research & Development 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, ML Flow, and other tools. The role also includes responsibility for following best practices to optimize and measure the performance of our models and algorithms against business goals.

MAIN DUTIES

• The following is a non-exhaustive list of responsibilities and areas of ownership of an AI / ML R&D Engineer:
• Design and develop machine learning models and algorithms for localization and business workflow processes, including machine translation, LLM finetuning, and quality assurance.
• Take ownership of key projects from definition to deployment, ensuring they meet technical requirements and maintain momentum until delivery.
• Evaluate and select appropriate machine-learning techniques and algorithms to solve specific problems.
• Implement and optimize machine learning models using Python, TensorFlow, and other relevant tools and frameworks.
• Perform statistical analysis and fine-tuning based on test results.
• Deploy machine learning models using techniques such as containerization with Docker and deployment to cloud infrastructure.
• Utilize AWS technologies (Sagemaker, EC2, S3) to deploy and monitor production environments.
• Stay updated with developments in the field and dedicate efforts to continuous learning.
• Document experiments, design, and deployment processes thoroughly and communicate effectively with stakeholders.
• Define and design solutions for machine learning problems, with guidance from senior engineers for system integration.
• Success indicators include accurate and efficient models, positive team collaboration, continuous learning, clear communication, and ethical AI development.

REQUIREMENTS

• Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field; PhD is a plus.
• Minimum 3+ years of experience as a Machine Learning Engineer or similar role.
• Strong proficiency in Python for production-grade coding.
• Excellent communication and documentation skills.
• Deep knowledge of machine learning techniques, including supervised, unsupervised, deep learning, and reinforcement learning.
• Hands-on experience with frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Experience with NLP techniques and tools.
• Ability to explain complex technical concepts to non-technical stakeholders.
• Experience managing projects from conception to deployment and mentoring juniors.
• Proficiency with AWS services (EC2, S3, Sagemaker, SNS) and deployment strategies, including Docker and GPU deployments.

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