Machine Learning Engineer
2 weeks ago
Having worked in a startup and /or
Product based organisation is a added advantage.
Company DescriptionGiggso is a No-Code ModelOps Observability platform founded in 2018. Our platform provides a consolidated and integrated solution for data science, engineering teams, and business executives. We help AI ML teams with incident management, automation, remediation, and self-healing, while also offering capabilities for model risk management and security compliance. Giggso's platform is web 3.0 and blockchain-enabled, bringing together messages and notifications to drive intelligent decision-making.
Role Description
This is a full-time on-site role for a Machine Learning Engineer at Giggso located in Chennai. The Machine Learning Engineer will be responsible for day-to-day tasks related to pattern recognition, computer science, neural networks, statistics, and algorithms. They will work closely with the team to develop and implement machine learning models and algorithms
To join our team, you should possess the below skills:
Experience in productizing and deployment of Machine Learning solutions.Thorough understanding of the full ML pipeline, starting from data collection to model building to inference.Thorough understanding of model monitoring (detecting model variations, etc.) and also the retraining/redeployment processExperience with Python and at least a few frameworks/libraries (TensorFlow/ Keras / PyTorch / spaCy / fastText / Scikit-learn etc.)Experience or Knowledge in MLOPS and Model OPS.NLP (Natural Language Processing) experience, including text classification, entity extraction, and content summarization.Strong verbal and written communication skills to express data science concepts and solutions to product managers, data scientists, business partners of varying technical levels, and influence and negotiate to reach alignment on executing strategies and improving models.
Your responsibilities:
Develop, train, deploy and monitor Machine Learning models.
Utilize published/existing models to meet business requirements, making necessary tweaks for improving efficiencies and adapting to use-case variations.
Optimize machine learning model training and inference time.
Perform Machine Learning model training, deployment, monitoring, and retraining.Independently handle end-to-end tasks, including data collection, preparation/annotation, and validation of outcomes.
Define and develop ML infrastructure to enhance the efficiency of ML development workflows.Collaborate with other Engineers, data scientists, product managers, and engineers to formulate innovative ideas, and test / implement them through advanced data science techniques.
Innovation brains - technologists who need to break free from standard programming roles to develop vision at speed and scale and become owners of a feature or product within our platform.
Ideal candidates are enterprising youngsters who are good in communication and technology and have a flair to accomplish and be a star. The social and hobbies of the individual matter to us, we need free minds who can adapt to agile needs.
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