Machine Learning Engineer, Flawless AI

• Bachelor or Masters Degree in Computer Vision, Machine Learning, or related fields
• Minimum of 2 years of relevant work experience
• Strong communication and interpersonal skills with team and cross-functional partners Excellent Python. and object-oriented programming skills
• Experience developing with or using deep learning frameworks (PyTorch, TensorFlow, ONNX, etc.)
• Experience building scalable ML pipelines for multi-media modalities with tools such as AirFlow, Flyte, Kubeflow, or Prefect
• Experience with various cloud data storage technologies on AWS, Azure, or GCP
• Experience with software development best practices and version control systems

Desirable

• As a Machine Learning Engineer, you will be working with a team focusing on large-scale (synthetic) data generation, curation, analysis, and labeling, as well as prototyping and deploying flexible ML frameworks for scalable experimentation and benchmarking of new research developments
• As a member of the science department, you will be expected to create flexible and scalable ML frameworks to transform exploratory prototypes into scalable and deployable experimentation and product pipelines through solid ML design patterns, MLOps principles, and quality software design
• This role will partner closely with our Research, Applied Science, Engineering, Film Innovation, and VFX teams in the US and UK offices
• In this role, you will be expected to be a subject matter expert in modern computer vision concepts, scalable Machine/Deep Learning system development, model and data optimization, and orchestration
• Our work in automated visual translation is just the beginning, and we are developing countless exciting products based on the application of our proprietary, cornerstone research
• Develop flexible and scalable ML frameworks for prototyping and robust experimentation at scale
• Deliver Machine/Deep Learning system optimizations, including but not limited to cost-effective orchestration, data and model quantization, and model parallelization
• Partner closely with Science Producer, Applied Science, VFX, Product, and Engineering teams to ensure successful delivery of new research technologies and Machine/Deep Learning systems

• Our interview process is four rounds over Zoom:
• 30-45 minute call with our recruiting team (We want to discuss your interests and motivations as well as the practical details and make sure that Flawless would be a good fit for you)
• 45 minute technical screen with the Senior ML Engineer to discuss Flawless and your past work
• 1 hour ML system design with ML Team
• 1 hour System level coding / considerations evaluation discussing code architecture, troubleshooting, and scalability, deployment and project management abilities with ML Team
• Your Recruiter and hiring manager will be your main point of contact and prepare you for interviews
• You’ll meet 5-6 people from across the Science teams. (We make sure that you have time in each interview to ask them questions). If we don’t give an offer, we’ll provide feedback!