
Controls - AI Developer
- Bangalore, Karnataka
- Permanent
- Full-time
- Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, NLP, computer vision) to address specific application requirements.
- Implement robust MLOps practices, including model versioning, deployment automation, monitoring, and retraining pipelines.
- Collaborate with data engineers to ensure data quality, availability, and optimal feature engineering for ML models.
- Integrate deployed ML models seamlessly into the existing application architecture, ensuring high performance and reliability.
- Conduct experimentation, A/B testing, and performance tuning to continuously improve model accuracy and efficiency.
- Write clean, well-documented, and testable code in Python or other relevant programming languages.
- Research and stay abreast of the latest advancements in machine learning, deep learning, and artificial intelligence.
- Troubleshoot and resolve issues related to model performance, data pipelines, and deployment.
- Participate in code reviews, technical discussions, and contribute to the overall architectural design of ML systems.
- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related quantitative field.
- Proven 2+ years of professional experience as a Machine Learning Engineer or in a similar role.
- Strong proficiency in Python and relevant ML libraries (e.g., scikit-learn, pandas, NumPy).
- Experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch, Keras).
- Solid understanding of machine learning algorithms, statistical modeling, and data structures.
- Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and their ML services.
- Experience with version control systems (e.g., Git).
- Ability to translate business problems into technical ML solutions.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
- Familiarity with containerization technologies (e.g., Docker, Kubernetes).
- Experience with big data technologies (e.g., Spark, Hadoop) and data warehousing.
- Knowledge of software development best practices (e.g., CI/CD, unit testing).
- Publications or contributions to open-source ML projects.