Presentation / Installation
Sr Data Engineer - Deep Learning
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Flawless AI
·
Los Angeles, CA
SessionJob Postings
DescriptionFlawless is an award winning film technology company pioneering the generative AI revolution in filmmaking. Solving some of the biggest problems filmmakers face by empowering them with groundbreaking AI powered post production tools, allowing on screen dialogue to be visually changed without the need to reshoot or go back to set. The world’s first system has won multiple awards including TIME Best Inventions.
Founded in 2020 by Hollywood director, Scott Mann and serial technology entrepreneur Nick Lynes, Flawless is opening a world of new possibilities for filmmakers whilst ensuring the responsible adoption of generative AI. With headquarters in London and LA, Flawless has established an exceptional team of 100 world leaders in science, film and technology that have come from the likes of Adobe, Google, Lionsgate, NASA, Sony, Facebook, Microsoft and Apple (click here to find out more).
Flawless are looking for a Sr Data Engineer - Deep Learning.
You will be working in an environment based on trust, autonomy and collaboration, and this is a great opportunity for someone who wants to be part of a growing company in its most exciting stage of development. You can play a part in shaping the future of a company that’s caring, creative and collaborative.
The data team is responsible for sourcing, annotating, curating, and deploying large multi-modal datasets within the film media domain. The data team works with core and applied ML, lighting, staging, engineering, and film innovation teams to understand data requirements and deliver high-quality datasets that power next-generation AI models. The team is also responsible for data versioning, data DevOps, and persistent storage.
Our work in automated visual translation is just the beginning, we’re developing countless exciting products based on the application of our proprietary, cornerstone research.
This is an unbelievable opportunity to join a team operating at the cutting edge of the generative revolution, don't hesitate, reach out today.
Qualifications
Minimum Requirements
Bachelor's degree in computer science, machine learning, computer vision, or a related field
4+ years of experience preparing large datasets for deep learning and neural network models
4+ years of experience writing and testing modularized, production-level Python code
Experience with deep learning frameworks such as PyTorch, Tensorflow, Keras, or MXNET
Experience building scalable ML pipelines for image and video modalities with tools such as Flyte, Prefect, AirFlow, or Kubeflow
Experience with data collection, labeling, cleaning, and generation with tools such as LabelBox, SuperAnnotate, Scale Ai, or V7
Preferred Requirements
MS or PhD in computer science, machine learning, computer vision, or a related field
Experience with CI / CD automation using tools such as GitHub Actions or GitLab
Experience setting up and configuring cloud infrastructure resources with tools such as Terraform or CloudFormation
Experience with various cloud data storage technologies on AWS, GCP, or Azure
Experience writing production-grade C++
Experience with audio, text, or 3D data modalities
Founded in 2020 by Hollywood director, Scott Mann and serial technology entrepreneur Nick Lynes, Flawless is opening a world of new possibilities for filmmakers whilst ensuring the responsible adoption of generative AI. With headquarters in London and LA, Flawless has established an exceptional team of 100 world leaders in science, film and technology that have come from the likes of Adobe, Google, Lionsgate, NASA, Sony, Facebook, Microsoft and Apple (click here to find out more).
Flawless are looking for a Sr Data Engineer - Deep Learning.
You will be working in an environment based on trust, autonomy and collaboration, and this is a great opportunity for someone who wants to be part of a growing company in its most exciting stage of development. You can play a part in shaping the future of a company that’s caring, creative and collaborative.
The data team is responsible for sourcing, annotating, curating, and deploying large multi-modal datasets within the film media domain. The data team works with core and applied ML, lighting, staging, engineering, and film innovation teams to understand data requirements and deliver high-quality datasets that power next-generation AI models. The team is also responsible for data versioning, data DevOps, and persistent storage.
Our work in automated visual translation is just the beginning, we’re developing countless exciting products based on the application of our proprietary, cornerstone research.
This is an unbelievable opportunity to join a team operating at the cutting edge of the generative revolution, don't hesitate, reach out today.
Qualifications
Minimum Requirements
Bachelor's degree in computer science, machine learning, computer vision, or a related field
4+ years of experience preparing large datasets for deep learning and neural network models
4+ years of experience writing and testing modularized, production-level Python code
Experience with deep learning frameworks such as PyTorch, Tensorflow, Keras, or MXNET
Experience building scalable ML pipelines for image and video modalities with tools such as Flyte, Prefect, AirFlow, or Kubeflow
Experience with data collection, labeling, cleaning, and generation with tools such as LabelBox, SuperAnnotate, Scale Ai, or V7
Preferred Requirements
MS or PhD in computer science, machine learning, computer vision, or a related field
Experience with CI / CD automation using tools such as GitHub Actions or GitLab
Experience setting up and configuring cloud infrastructure resources with tools such as Terraform or CloudFormation
Experience with various cloud data storage technologies on AWS, GCP, or Azure
Experience writing production-grade C++
Experience with audio, text, or 3D data modalities
brian.prather@flawlessai.com
2023-07-17
Event Type
Job Posting
TimeSunday, 6 August 20238am - 9:30am PDT
Location
Session TimeSunday, 6 August 20238am - 9:30am PDT
Location
