Machine Learning Engineer Graduate Fresher Jobs in Pune

We are seeking a talented AI/ML Engineer to design, develop, and deploy machine learning models that solve real-world business problems.Key ResponsibilitiesDevelop, train, and optimize machine learning and deep learning models.Design and implement AI solutions for automation, prediction, and data analysis.Work with large datasets to clean, preprocess, and engineer features.Deploy models into production environments and monitor performance.Build scalable ML pipelines and integrate models with applications.Conduct experiments, model evaluations, and performance tuning.Collaborate with cross-functional teams including data engineers and product managers.Stay updated with the latest research and advancements in AI/ML.Note: Only Pune-based candidates can eligible to apply.

***Responsibilities:***1. Contribute to the development of software and solutions, emphasizing ML/NLP as a key component, to productize research goals and deployable services.2. Collaborate closely with the frontend team and research team to integrate machine learning models into deployable services.3. Utilize and develop state-of-the-art algorithms and models for NLP/ML, ensuring they align with the product and research objectives.4. Perform thorough analysis to improve existing models, ensuring their efficiency and effectiveness in real-world applications.5. Engage in data engineering tasks to clean, validate, and preprocess data for uniformity and accuracy, supporting the development of robust ML models.6. Stay abreast of new developments in research and engineering in NLP and related fields, incorporating relevant advancements into the product development process.7. Actively participate in agile development methodologies within dynamic research and engineering teams, adapting to evolving project requirements.8. Collaborate effectively within cross-functional teams, fostering open communication and cooperation between research, development, and frontend teams.9. Actively contribute to building an open, transparent, and collaborative engineering culture within the organization.10. Demonstrate strong software engineering skills to ensure the reliability, scalability, and maintainability of deployable ML services.11. Take ownership of the end-to-end deployment process, including the deployment of ML models to production environments.12. Work on continuous improvement of deployment processes and contribute to building a seamless pipeline for deploying and monitoring ML models in real-world applications.

***Responsibilities:***1. Contribute to the development of software and solutions, emphasizing ML/NLP as a key component, to productize research goals and deployable services.2. Collaborate closely with the frontend team and research team to integrate machine learning models into deployable services.3. Utilize and develop state-of-the-art algorithms and models for NLP/ML, ensuring they align with the product and research objectives.4. Perform thorough analysis to improve existing models, ensuring their efficiency and effectiveness in real-world applications.5. Engage in data engineering tasks to clean, validate, and preprocess data for uniformity and accuracy, supporting the development of robust ML models.6. Stay abreast of new developments in research and engineering in NLP and related fields, incorporating relevant advancements into the product development process.7. Actively participate in agile development methodologies within dynamic research and engineering teams, adapting to evolving project requirements.8. Collaborate effectively within cross-functional teams, fostering open communication and cooperation between research, development, and frontend teams.9. Actively contribute to building an open, transparent, and collaborative engineering culture within the organization.10. Demonstrate strong software engineering skills to ensure the reliability, scalability, and maintainability of deployable ML services.11. Take ownership of the end-to-end deployment process, including the deployment of ML models to production environments.12. Work on continuous improvement of deployment processes and contribute to building a seamless pipeline for deploying and monitoring ML models in real-world applications.