Member of Technical Staff (Machine Learning Engineer)

3 months ago

Remote, WorldwideSenior

H1B Sponsor

Responsibilities

Translate cutting-edge research into production-ready machine learning systems.
Design, build, and deploy end-to-end ML models and pipelines.
Develop and optimize models for image and video processing.
Own experimentation, training, fine-tuning, evaluation, and deployment across the ML lifecycle.
Prototype with open-source models and adapt them for product needs.
Conduct experiments, analyze results, and iterate to improve model performance.
Build low-latency, real-time ML deployment and inference systems.
Collaborate with researchers and cross-functional product, engineering, and design teams to deliver ML solutions at scale.

A minimum of an MS or PhD in Computer Science, Electrical Engineering, or a related field is required.
At least 5 years of experience with Python and proficiency in Java, C++, or Scala are required.
Strong research experience and familiarity with top conferences such as CVPR, ICCV, and NeurIPS are required.
Strong understanding of diffusion models, multithreading, memory management, CNNs, and Transformers is required.
Experience with PyTorch or TensorFlow and end-to-end ML deployment and inference systems is required.
Experience deploying ML models in cloud environments, preferably AWS, and using experiment tracking systems and ML workflows is required.
Preferred qualifications include low-level optimization and CUDA experience, productionizing and scaling ML models, open-source contributions, MLOps tools or distributed training systems, relational databases such as Postgres or MySQL, and large-scale data tools such as Spark.

11-50 employees

AI research and product company with a mission to build models that understand the physical world.