Machine Learning Engineer

4 weeks ago

delhi, India Jupitos Technologies LLC Full time
Position : Machine Learning Engineer
Location : Remote
Experience : 7 to 12 years
Notice Period : Immediate
Role Summary :
We're seeking a Machine Learning Engineer (MLE) for one of our customer with a strong development background to lead the development and implementation of cutting-edge machine learning solutions. This role is pivotal in driving innovation and efficiency across our projects. The ideal candidate will have robust experience in machine learning, data processing, and software development, capable of seamlessly integrating existing models and deploying new ones into production.
Key Responsibilities :
Develop, optimize, and deploy machine learning models to achieve project objectives.
Process and analyze large datasets to inform model development and enhancements.
Maintain and enhance existing machine learning models to meet accuracy and performance standards.
Collaborate with cross-functional teams to seamlessly integrate machine learning solutions into our operational framework.
Utilize software development tools to maintain a robust, scalable codebase.
Apply a variety of machine learning techniques (e.g., statistics, clustering, classification, outlier analysis) to solve complex problems.
Basic Qualifications :
Proficiency in Python and familiarity with key machine learning packages such as numpy, pandas, scikit-learn, and xgboost.
Understanding of data structures, data modeling, software architecture, and tools including Git and virtual environments.
Demonstrated ability to apply machine learning techniques to real-world problems.
Experience in deploying machine learning models in code and working with existing models.
Strong problem-solving skills and the ability to work independently or as part of a team.
Development experience is essential; candidates without analytical or analysis exposure will not be considered.
Preferred Qualifications :
Experience in building and accessing API endpoints.
Cloud computing experience, particularly with AWS.
Experience with deploying open source deep learning models, with a preference for those related to Life Sciences.
Proficiency in Deep Learning frameworks, such as PyTorch.
Experience in building and managing MLOps pipelines.

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