Engineering Manager (Computer Vision)

Job Responsibilities

• You will manage and lead the Computer Vision Innovation, provide guidance and support to its team members.
• You are accountable for supervising and developing the automated Imaging, 3D and Video solutions impacting industries Automobile, Fashion, Food, Real Estate and eCommerce.
• You are responsible for recruiting, resource management and resource allocation.
• You are responsible for delivering projects on time, in budget and with the expected quality as well.
• You will spend time reading new research papers and are guiding team to create the customized algorithm solving challenges which are not in production anywhere in the globe.
• You will work with the Data team to ensure that the data pipelines of various problems are well set up and models are being constantly trained and updated.
• You will work alongside product team to ensure that AI capabilities are built as democratized tools that provided internal as well external stakeholders to innovate on top of it and make our customers successful.
• You will work with Infra Engineering teams to ensure that the models are scalable, fast and have zero to no downtime.

Key Qualifications

• PhD in Computer Science, Engineering or a related subject from a prestigious university or Masters with deep Computer Vision and GANs project experience.
• Authored publications at peer-reviewed AI conferences (e.g. NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).
• 5+ yrs Work Experience in Computer Vision, Graphics and Image Processing
• 3+ years experience in leading high performing deep learning research team in a product based environment
• Experience with a wide variety of Deep Learning Models (i.e. LSTM, RNN, CNN, GAN)
• Good Exposure on Deep Learning frameworks like TensorFlow/ Pytorch.
• Great interpersonal and communication skills
• Experience in developing and debugging in C/C++, Python, or C#

Desired Technical Skills

• Prompt engineering.
• Neural Radiance Fields (NeRF).
• Gaussian Splatting.
• Differentiable rendering.
• Diffusion models.
• 3D diffusion/generative models.
• Signed distance fields (SDF).

Place of work