The AI Machine Learning Research & Development 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, ML Flow, and other technologies.
The role involves following best practices to optimize and measure the performance of models and algorithms against business goals.
Responsibilities include designing and developing machine learning models and algorithms for various aspects of localization and business workflow processes, including machine translation, LLM finetuning, and quality assurance.
The engineer will take ownership of key projects from definition to deployment, ensuring they meet technical requirements and maintain momentum until delivery.
Evaluation and selection of appropriate machine-learning techniques and algorithms to solve specific problems is required.
Implementation and optimization of machine learning models and technologies using Python, TensorFlow, and other relevant tools and frameworks are essential.
The role includes performing statistical analysis and fine-tuning using test results.
Deployment of machine learning models and algorithms using techniques such as containerization with Docker and deployment to cloud infrastructure is necessary.
The engineer will use AWS technologies (including but not limited to Sagemaker, EC2, S3) to deploy and monitor production environments.
Keeping abreast of developments in the field and a dedication to learning in the role is expected.
Diligent documentation and thoughtful communication about ML experimentation, design, and deployment are required.
The project scope involves defining and designing solutions to machine learning problems, with integration into larger systems guided by more senior engineers.
Success indicators include effective model development, positive team collaboration, continuous learning and improvement, clear communication, and adherence to ethical AI practices.
Requirements:
A Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a similar field is required; a PhD is a plus.
A minimum of 3+ years of experience as a Machine Learning Engineer or in a similar role is necessary.
The candidate must have the ability to write robust, production-grade code in Python.
Excellent communication and documentation skills are required.
Strong knowledge of machine learning techniques and algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning is essential.
Hands-on, high proficiency experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn is required.
Experience with natural language processing (NLP) techniques and tools is necessary.
Strong communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders, are essential.
Experience taking ownership of projects from conception to deployment and mentoring more junior team members is required.
Hands-on experience with AWS technologies including EC2, S3, and other deployment strategies is necessary, with experience in SNS and Sagemaker being a plus.
Experience with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, and GPU deployments, is required.
Benefits:
The position offers the opportunity to work in a dynamic and innovative environment focused on machine learning and AI.
Employees will have access to a global network of resources and the chance to collaborate with teams across North America, Europe, and Asia.
Continuous learning and professional development opportunities are provided to keep up with advancements in the field.
The role allows for significant ownership of projects, contributing to personal and professional growth.
The company promotes ethical and responsible AI development, ensuring a commitment to fairness and bias-free models.
