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Staff Software Engineer, Machine Learning

3 months ago

Delhi, India Zippin Full time
We are seeking a passionate Staff Machine Learning (ML) Engineer with extensive experience in developing and deploying state-of-the-art Machine Learning services in the computer vision space, both on cloud platforms and edge devices. In this role, you will engage in the full lifecycle of building machine learning services, from conceptualizing ideas and preparing data to selecting features, training, evaluating, and deploying models.

This position may be remote in India.

Required Qualifications

- Bachelor's degree in computer science/electrical engineering or equivalent practical experience.- 8+ years of relevant work experience in software development.- 4+ years of experience with computer vision, machine learning or deep Learning.- Strong grasp of statistical machine learning, linear algebra, and deep learning for computer vision- Experience with one or more general purpose programming languages including but not limited to: C/C++, or Python.- Experience with PyTorch or TensorFlow or other ML Frameworks.- Experience in deploying ML solutions in production environments.

Desirable Qualifications

- Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.- Strong research experience with a track record of publishing or internship experience focussed in one or more of the following: Computer Vision, Natural Language Processing, pattern recognition, recommendation systems, or similar.- Experience in deploying ML solutions on large scale systems.- Excellent communication and documenting skills.

In this role, you will

- Design and implement ML components, systems and tools to automate and enable checkout free shopping.- Apply research methodologies to identify the machine learning models to solve a business problem and deploy the model at scale.- Own the ML pipeline from data collection, through the prototype development to production.- Develop high-performance, scalable, and maintainable inference services that communicate with the rest of our tech stack.