Remote Staff R&D AI Engineer

Description:

• The company is establishing the first distributed AI infrastructure dedicated to personalized AI, focusing on scalability and flexibility for a data-driven society.
• As a Staff R&D AI Engineer, you will lead the development of advanced AI systems that integrate computer vision, natural language understanding, and action learning.
• You will architect and implement Vision-Language-Action (VLA) models, advance reinforcement learning applications, and enhance multimodal AI integration.
• The role requires deep expertise in computer vision and large language models, along with hands-on experience in reinforcement learning to create intelligent systems.
• Responsibilities include designing VLA models, architecting reinforcement learning systems, optimizing computer vision pipelines, and developing large language models.
• You will implement RLHF systems, create multimodal training pipelines, research novel AI architectures, and collaborate with engineering teams to integrate AI models.
• The position involves optimizing model inference performance, leading technical initiatives, mentoring junior engineers, and staying current with AI research.
• You will also present findings at conferences and publish research to contribute to the field.

Requirements:

• A minimum of 7 years of experience in AI/ML engineering, with at least 4 years focused on deep learning and neural network development.
• Strong understanding of reinforcement learning algorithms and their applications, such as PPO, SAC, and TD3.
• Expertise in both computer vision and natural language processing, with hands-on model development experience.
• Proficiency in PyTorch and/or TensorFlow, with experience in training and deploying large-scale models.
• Experience with transformer architectures, attention mechanisms, and fine-tuning large language models.
• Hands-on experience with computer vision tasks, including object detection, semantic segmentation, and visual tracking.
• Strong programming skills in Python, with experience in distributed training and model optimization.
• Understanding of sequential decision-making and control systems fundamentals.
• Experience with MLOps practices, including model versioning, monitoring, and deployment pipelines.
• Proven ability to work independently on complex research problems and deliver practical solutions.
• Strong communication skills and experience collaborating with cross-functional engineering teams.

Benefits:

• The position offers a competitive salary and performance-based incentives.
• A comprehensive health, dental, and vision benefits package is provided.
• Employees receive a $200/month Health and Wellness Stipend and a $400/year Continuing Education Credit.
• The company offers a flexible work week and free parking for in-office employees.
• Unlimited Paid Time Off (PTO) is available, along with parental and bereavement leave.
• Supplemental Life Insurance is also part of the benefits package.