We are seeking a highly motivated and talented Machine Learning Engineer with a strong background in anomaly detection to join our growing AI/ML team. In this role, you will be responsible for developing and deploying cutting-edge machine learning models to identify and predict anomalous events across various domains within our business. You will work closely with data scientists, engineers, and product managers to solve challenging problems and deliver impactful solutions.
Responsibilities:
- Research, design, and develop advanced anomaly detection algorithms (e.g., isolation forests, one-class SVM, autoencoders, time series forecasting)
- Train and evaluate machine learning models on large and complex datasets.
- Develop and deploy real-time anomaly detection systems using scalable and efficient technologies.
- Collaborate with cross-functional teams to understand business needs and translate them into technical requirements.
- Monitor model performance, identify areas for improvement, and continuously retrain and optimize models.
- Stay abreast of the latest advancements in anomaly detection and machine learning research.
- Contribute to the development of the best practices and guidelines for machine learning model development and deployment.
- Communicate technical concepts effectively to both technical and non-technical audiences.
Qualifications:
- Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related field.
- 8+ years of experience in developing and deploying machine learning models in production environments.
- Strong understanding of anomaly detection techniques and algorithms.
- Proficiency in Python and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with data preprocessing, feature engineering, and model evaluation.
- Experience with cloud platforms (e.g., AWS, GCP, Azure) is a plus.
- Excellent communication and collaboration skills.
- Strong analytical and problem-solving skills.
- Passion for machine learning and a strong desire to learn and grow.
Nice to have:
- Experience with time series analysis and forecasting.
- Experience with deep learning models (e.g., recurrent neural networks, convolutional neural networks).
- Experience with MLOps practices (e.g., model monitoring, versioning, and deployment).
- Publications in top-tier machine learning conferences or journals.
The pay range for this role is $110,000 - $135,000* per annum including any bonuses or variable pay. Tech Mahindra also offers benefits like medical, vision, dental, life, disability insurance and paid time off (including holidays, parental leave, and sick leave, as required by law).
