Senior Software Engineer

Role : Machine Learning Engineer Experience : 5-10 Years Location : Bangalore/Hyderabad Notice Period : Less than 30 Days Key Responsibilities: Model Development : Design, develop, and implement machine learning models for various applications, ensuring they are impactful and solve real-world business challenges. Algorithm Selection : Choose and optimize machine learning algorithms and libraries (e.g., TensorFlow, PyTorch) based on project needs. Model Integration : Seamlessly integrate machine learning models into existing production systems. ML Pipeline Development : Build and maintain scalable ML pipelines for training, deployment, and monitoring. Model Monitoring : Continuously monitor model performance and proactively address any issues or improvements. Collaboration : Work closely with data scientists, engineers, and other stakeholders to translate business requirements into technical solutions. Continuous Learning : Stay current on the latest advancements in machine learning, contributing to innovation and the overall success of the team. Production Deployment : Leverage experience in deploying machine learning models into production environments, ensuring high reliability and efficiency. Azure Expertise : Be proficient with the Azure ecosystem, ensuring smooth deployment and management of models. Required Skills: Programming Languages : Strong proficiency in Python and SQL . ML Tools and Frameworks : Experience with Databricks , TensorFlow , and PyTorch . Cloud Experience : In-depth knowledge of Azure and the Azure ML platform. Machine Learning : Expertise in machine learning models, pipelines, and deployment strategies. AI Techniques : Familiarity with NLP (Natural Language Processing) and Generative AI techniques (experience with these will be a plus). Collaboration : Ability to collaborate effectively with data scientists and software engineers. Qualifications: A degree in a relevant field (Computer Science, Engineering, or related fields). Experience : Minimum 5-10 years of experience in machine learning engineering, with a proven track record in deploying models to production. Certifications : Relevant certifications (e.g., Azure, Machine Learning) are a plus.