Lead Software Engineer, Machine Learning

Work Environment

• This is a fully remote position within the U.S., offering you the flexibility to design your workday to maximize productivity and balance. We provide you with the autonomy to work in a way that suits you best as long as you’re able to collaborate effectively with our team, particularly during Pacific Time zone business hours.
• While our team is distributed across the country, we believe in the power of face-to-face connections. You'll have the opportunity to meet with colleagues in person at least once a year, fostering deeper collaboration and camaraderie. These occasional in-person meetings will be scheduled with plenty of advance notice, and we'll cover all travel expenses, making sure you’re comfortable and prepared.
• In addition to a competitive salary, we offer comprehensive health benefits, flexible time away from work, and support for ongoing professional development. We prioritize your well-being and personal growth as much as your professional success.

Responsibilities

• Train, improve, evaluate, integrate, and deploy machine learning models for a variety of computer vision use cases, such as object detection, segmentation, feature matching, and depth estimation.
• Optimize the performance of ML models and systems for speed, accuracy, and resource efficiency.
• As a self-driven engineer, you'll take ownership of deliverables from design to implementation, release, and support. You'll also pick up the knowledge you need to complete the job.
• Collaborate with ML, Computer Vision, and DevOps Engineers to automate and streamline the ML model training, testing, and deployment pipelines.
• Building and maintaining high-quality datasets, ensuring data gets labeled properly and errors corrected, targeting additional relevant data, and evaluating the impact on the models.
• Lead the design, development, and maintenance of scalable and efficient machine learning infrastructure, including training, CI/CD, monitoring, and other automation.
• Lead a team of talented engineers with ample opportunities for professional growth and leadership development. We invest in our people, providing continuous learning opportunities and the chance to shape the future of machine learning.
• Stay up-to-date with the latest ML advancements and evaluate their potential application to our workflows.
• Collaborate with cross-functional teams to understand business requirements and deliver ML solutions that meet organizational goals.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field with 5+ years of professional experience in ML Data Science and MLOps.
• Experience designing, building, deploying, debugging and maintaining large-scale production ML systems to solve computer vision problems.
• Ability to timebox experiments, iterate effectively and leverage excellent problem-solving skills to triage routes to success.
• Experience with modern ML in Pytorch, Keras, TensorFlow or equivalent.
• Experience building and improving models like Mask2former, MaskRCNN, Resnet, Unet.
• Experience running and monitoring multiple ML experiments in cloud environments concurrently.  
• Experience using and extending MLOps platforms (e.g. WandB, Vertex AI, Metaflow, mlflow, Databricks)
• High degree of comfort with UNIX and training and inference on cloud instances cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Experience with CI/CD tools (e.g., Jenkins, GitHub CI).
• Experience as a productive remote employee able to overlap standup AM meetings PST.
• Strong communication and leadership skills.

Preferred Qualifications & Expertise

• Proficient in leading and managing large MLOps projects.
• Proficiency in developing and debugging C++
• Proficient with 3D perception and 3D reconstruction pipelines.