
Be 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

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BS/MS in computer science or prior experience as a software engineer
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Proficient understanding of web markup, including HTML5, CSS3
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Great attitude to ask questions, learn and suggest process improvements.
Pays great attention to detail and helps identify edge cases.
Gives equal importance to planning, coding, code reviews, documentation, and testing.
Highly motivated and coming up with fresh ideas and perspective to help us move towards our goals faster.
Follows release cycles and absolute commitment to deadlines.
Our tech stack is Django framework (python), ReactJS, PostgreSQL, Redis, COSMOS DB, and Elasticsearch.










