Machine Learning Engineer

Overview

This is a Hybrid role (3x days a week) based in Redmond, WA. The contract will start at 11 months and can extend up to 18 months. While most days will be PST working hours there will be occasional days where there is a 7am meeting due to team members located internationally.

Our client is seeking a Machine Learning Engineer to advance the development and improvement of our software foundation and tools vital for training state-of-the-art AI models. Your role will be centered on creating strong, scalable, and efficient training infrastructures and frameworks facilitating the full spectrum of the machine learning process, from handling data to deploying models. In collaboration with researchers and software engineers, you’ll ensure that training systems are smoothly integrated and functioning, expanding the limits of AI’s capabilities, especially in practical robotics scenarios. Additionally, you will investigate innovative methods to effectively utilize diverse datasets within our training framework. The purpose of this team is AI research team. Teach robots to do new skills. Software and hardware engineers integrate.

In this dynamic role, you will:

• Develop and maintain efficient, scalable, and distributed training systems for large-scale AI models, encompassing data preprocessing, training orchestration, and model evaluation.
• Optimize training processes for enhanced performance and resource utilization, ensuring scalability and reliability.
• Partner with researchers to build and implement training and evaluation pipelines for cutting-edge algorithms.
• Design and develop benchmarks for evaluating ML model performance.
• Conduct training and fine-tuning of foundation models specifically for robotic applications.
• Monitor and analyze pipelines, identifying and resolving bottlenecks to boost efficiency and performance.
• Ensure the robustness and reliability of the training infrastructure through automated testing and continuous integration.

Must-Have Qualifications:

• 2+ years of experience with Linux
• 2+ years of experience with Python
• 2+ years of experience with Configuration Management
• 2+ years of experience with ROS/ROS2
• 2+ years of experience with TensorFlow
• 2+ years of experience with Machine Learning packages
• Bachelor’s degree in Computer Science or a related field

Nice-to-Have Qualifications:

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
• Strong background in distributed computing, parallel processing techniques, handling large-scale datasets and data preprocessing.
• Deep understanding of state-of-the-art machine learning techniques and models.
• Experience with cloud-based training environments (AWS, Google Cloud, Azure).
• Experience in developing and maintaining software tooling and infrastructure for machine learning.
• Deep understanding and practical experience with software engineering principles, including algorithms, data structures, and system design.
• Experience with continuous integration and automated testing frameworks.

The target hiring compensation range for this role is $74 to $82 an hour. Compensation is based on several factors including, but not limited to education, relevant work experience, relevant certifications, and location.

About Aquent Talent:
Aquent Talent connects the best talent in marketing, creative, and design with the world’s biggest brands.
Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. We also offer free online training through Aquent Gymnasium. More information on our awesome benefits!
Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We’re about creating an inclusive environment—one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.