Senior Machine Learning Engineer (Python | PyTorch/TensorFlow | Snowflake | Databricks | MLOps)

Job Title: Senior Machine Learning Engineer (Python | PyTorch/TensorFlow | Snowflake | Databricks | MLOps) Company: datavruti Job Category: Machine Learning Roles & Responsibilities: Hiring for: A US\-based, AI\-first data solutions company founded by seasoned technology leaders. Role: Data Scientist Job Description We are seeking an Advanced Machine Learning Engineer to design, build, train, deploy, and operate scalable machine learning systems. This hands\-on ML engineering role focuses on implementing models and production systems \-not solely conducting data analysis or research. It requires strong Python and deep\-learning expertise, experience with frameworks such as PyTorch or TensorFlow, and the ability to own the end\-to\-end model lifecycle, from behavioral/event data preparation and feature engineering through model development, large\-scale training, deployment, inference optimization, and monitoring. The engineer will work with Snowflake, Databricks, Spark, and GPU\-based training infrastructure to deliver reliable, efficient, and maintainable ML capabilities. Key Responsibilities * Train models efficiently on GPU infrastructure using techniques such as mixed\-precision training, gradient accumulation, checkpointing, memory optimization, and distributed training strategies where appropriate. * Use PyTorch, TensorFlow, PySpark or equivalent frameworks to implement experiments and production\-ready training code; apply rigorous evaluation, error analysis, and reproducibility practices. * Build model\-training workflows covering event/token sequence preparation, tokenization, temporal and positional representations, self\-supervised pretraining, and downstream fine\-tuning when appropriate to the use case. * Design, implement, train, and optimize deep\-learning models; develop custom architectures where required, including transformer\- and attention\-based models for sequential or behavioral data. * Use Snowflake and SQL to access, query, and prepare enterprise data required by machine learning applications. * Use Databricks for scalable data processing, feature preparation, model development, and ML pipeline execution. * Develop and maintain reliable pipelines for data preparation, feature generation, training, batch scoring, and inference. * Use PySpark and distributed processing techniques where appropriate for large\-scale workloads. * Work with data engineering teams to integrate upstream data sources and ensure dependable data contracts, quality checks, and pipeline operation. * Productionize ML solutions and integrate them with services, APIs, data products, or downstream business workflows. * Implement model and code versioning, experiment tracking, reproducible builds, automated testing, and release practices. * Monitor model outputs and pipeline health; troubleshoot failures, data changes, drift, and performance degradation. * Improve operational reliability, scalability, observability, and maintainability of ML systems. * Collaborate with platform, cloud, and DevOps teams on deployment automation and production support. * Build observable production ML systems with appropriate logging, alerting, performance tracking, and operational safeguards. * Optimize inference latency, throughput, memory use, and serving cost through model architecture choices, batching, and serving\-side optimizations. * Develop clean, modular, documented, and maintainable code following engineering standards and design principles. * Contribute to technical design, code reviews, testing strategies, and architectural decisions for ML systems. * Own assigned ML engineering deliverables from technical design through implement Work Location: Chennai, Tamil Nadu, India Availability: Full time

Experience: 0-3 years Salary: Up to INR 30 LPA (based on the fitment) Key Skills: Machine Learning, Python, TensorFlow, PyTorch, Model Training, Feature Engineering Salary: Not disclosed