ML Lead

Cybage Software is a technology consulting organization and the head office is in Pune; you will get an opportunity to be a part of highly skilled talent pool of more than 7000 employees. We have our operations hub in GNR and Hyderabad as well and we have also marked our presence in USA, UK, Japan, Germany, Ireland, Canada, Australia, and Singapore. We provide seamless services and dependable deliveries to our clients from diverse industry verticals such as Media and Advertising, Travel and Hospitality, Digital Retail, Healthcare and Life Sciences, Supply chain and logistics, and Technology.

Machine Learning Engineer Cloud_Data_AI Group

We are seeking a skilled Machine Learning Engineer to develop and deploy ML models that address real-world business challenges. The ideal candidate will have hands-on experience in building scalable ML pipelines, implementing MLOps practices, and working with modern ML frameworks and cloud platforms.

Responsibilities:

• Build and deploy end-to-end ML pipelines, including data preprocessing, model training, and production deployment.
• Implement supervised, unsupervised, and deep learning models using frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Collaborate with data scientists and engineers to integrate ML models into production systems.
• Use MLOps tools like MLflow or Kubeflow for CI/CD and model lifecycle management.
• Monitor and optimize deployed models for performance and scalability.
• Stay updated on ML advancements and contribute to innovation within the team.

Required Skills:

• 2+ years of team leading
• Strong understanding of machine learning algorithms and statistical modeling.
• 3+ years of Proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tools.
• Knowledge of data preprocessing techniques and feature engineering.
• Excellent problem-solving and teamwork skills.

Preferred:

• Experience with distributed computing frameworks (e.g., Apache Spark).
• Exposure to AI/ML solutions for cloud ecosystems.
• Knowledge of containerization and orchestration (Docker, Kubernetes).