Senior Machine Learning Engineer - Hyderabad

Curapersonal Private Limited is seeking a highly skilled Senior Machine Learning Engineer with a significant track record to join our team in Hyderabad / Secunderabad, Telangana. This role is pivotal in designing, developing, and deploying advanced machine learning models and data-driven solutions that will shape our predictive and prescriptive analytics capabilities.

What You Will Do:

• Spearhead the development, training, and optimization of sophisticated machine learning models.
• Perform comprehensive data preprocessing, cleaning, and feature engineering on diverse structured and unstructured datasets.
• Collaborate closely with data scientists, data engineers, and software development teams to seamlessly deploy ML models into production environments.
• Implement and adapt cutting-edge machine learning algorithms and techniques to address complex business challenges.
• Proactively monitor model performance, accuracy, and detect drift, initiating retraining processes as necessary to maintain optimal functionality.
• Ensure the highest standards of data integrity, security, and compliance with all relevant privacy regulations.
• Integrate machine learning models into applications, APIs, and microservices for efficient real-time or batch prediction delivery.
• Write clean, efficient, maintainable, and reusable code adhering to robust software engineering best practices.
• Engage in research and evaluation of emerging ML frameworks, algorithms, and tools to drive innovation.

What You Bring:

• A Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a closely related field.
• A minimum of 26 years of professional experience in machine learning, data science, or AI engineering roles.
• Exceptional programming proficiency in Python or R.
• Hands-on experience with leading ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Proven expertise in data preprocessing, feature engineering, and conducting thorough exploratory data analysis (EDA).
• A strong understanding of model evaluation metrics, hyperparameter tuning, and cross-validation techniques.
• Demonstrable experience in deploying models using technologies like Docker, Kubernetes, or cloud-native services.

Bonus Points:

• Experience with deep learning models, Natural Language Processing (NLP), or Computer Vision.
• Familiarity with major cloud platforms including AWS Sagemaker, Azure ML, or GCP AI Platform.
• Exposure to MLOps practices and experience building automated ML pipelines.
• Knowledge of Continuous Integration and Continuous Deployment (CI/CD) principles for ML models.