Data Science
Machine Learning (ML)
KubernetesBe a part of the growth story of a rapidly growing organization in AI. We are seeking a passionate Machine Learning (ML) Engineer, with a strong background in developing and deploying state-of-the-art models on Cloud. You will participate in the complete cycle of building machine learning models from conceptualization of ideas, data preparation, feature selection, training, evaluation, and productionization.
On a typical day, you might build data pipelines, develop a new machine learning algorithm, train a new model or deploy the trained model on the cloud. You will have a high degree of autonomy, ownership, and influence over your work, machine learning organizations' evolution, and the direction of the company.
Required Qualifications
- Bachelor's degree in computer science/electrical engineering or equivalent practical experience
- 7+ years of Industry experience in Data Science, ML/AI projects. Experience in productionizing machine learning in the industry setting
- Strong grasp of statistical machine learning, linear algebra, deep learning, and computer vision
- 3+ years experience with one or more general-purpose programming languages including but not limited to: R, Python.
- Experience with PyTorch or TensorFlow or other ML Frameworks.
- Experience in using Cloud services such as AWS, GCP, Azure. Understand the principles of developing cloud-native application development
In this role you will:
- Design and implement ML components, systems and tools to automate and enable our various AI industry solutions
- 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
Shubham Vishwakarma
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Full Stack Developer - Averlon