Senior Machine Learning Engineer

Education
Bachelors or Masters degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative discipline; PhDs preferredSpecialization or research in applied machine learning, MLOps, or ML systems preferredExperience7+ years of experience designing, developing, and deploying ML models in production environments4+ years of experience in building predictive models like classification, time series modelling etc. 1+ year of experience in areas such as recommendation systems, pattern recognition, NLP Experience with production-grade Python (preferred), as well as Java or C/C++Hands-on experience with large-scale software architecture, APIs, and model versioning systemsSkills Expertise in Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learnProficient in cloud-based ML platforms (e.g., Azure ML, Google Cloud Platform, AWS SageMaker)Solid understanding of machine learning algorithms (e.g., classification, regression, SVMs, ARIMA, ensemble methods, deep learning, neural network)Strong foundation in probability theory and statistical modeling (generative and discriminative)Familiarity with DevOps/MLOps practices, CI/CD pipelines, GitHub Actions, Terraform Docker, and KubernetesAbility to communicate technical concepts clearly to both technical and non-technical takeholdersStrong collaboration skills with cross-functional teams (engineering, analytics, product)Ability to independently manage tasks and thrive in a remote-first or hybrid environmentPreferred Skills Experience in regulated industries (e.g., finance, healthcare, insurance)Excellent communication and stakeholder engagement skillsStrong understanding of deep learning architectures (e.g. CNNs, RNNs, Transformers, GANs) Strong in GPU based accelerating computing technologies (CUDA, Rapids, NeMo, NIM, etc.)Proficiency in model evaluation, distributed training, and hyperparameter optimizationProficient in Big Data Theory based large scale data streaming and in-memory database technologies (Spark, Kafka, Redis, Elastic Search)Strong in automated workflow technologies (GitHub Actions, Terraform, Helmet) and containerization technologies (Docker, Kubernetes)Proficient in API and Microservices technologies Track records in large-scale, real-time AI/GenAI/ML database and solution technologies Background in responsible AI/ML, model interpretability, and fairness auditingExperience : 7 +YearsLocation :Remote, Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune