Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I’m interested in this role because it combines my experience in data engineering, machine learning, MLOps, and production data pipelines with the opportunity to work on large-scale ML data systems. I enjoy building reliable data workflows, improving data quality, and creating infrastructure that enables ML teams to move faster. Torc’s work in autonomous driving is especially exciting because of the scale, technical challenges, and real-world impact of the technology.…I’m interested in this role because it combines my experience in data engineering, machine learning, MLOps, and production data pipelines with the opportunity to work on large-scale ML data systems. I enjoy building reliable data workflows, improving data quality, and creating infrastructure that enables ML teams to move faster. Torc’s work in autonomous driving is especially exciting because of the scale, technical challenges, and real-world impact of the technology.

SUBRAHMANYAM KOTA

AI Engineer, Data Scientist, Software Engineer, +2





I’m interested in this role because it combines my experience in data engineering, machine learning, MLOps, and production data pipelines with the opportunity to work on large-scale ML data systems. I enjoy building reliable data workflows, improving data quality, and creating infrastructure that enables ML teams to move faster. Torc’s work in autonomous driving is especially exciting because of the scale, technical challenges, and real-world impact of the technology.…I’m interested in this role because it combines my experience in data engineering, machine learning, MLOps, and production data pipelines with the opportunity to work on large-scale ML data systems. I enjoy building reliable data workflows, improving data quality, and creating infrastructure that enables ML teams to move faster. Torc’s work in autonomous driving is especially exciting because of the scale, technical challenges, and real-world impact of the technology.

Available to hire

I’m interested in this role because it combines my experience in data engineering, machine learning, MLOps, and production data pipelines with the opportunity to work on large-scale ML data systems. I enjoy building reliable data workflows, improving data quality, and creating infrastructure that enables ML teams to move faster. Torc’s work in autonomous driving is especially exciting because of the scale, technical challenges, and real-world impact of the technology.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Work Experience

AI/ML Engineer at ITON -INC

April 1, 2026 - Present

Design, develop, train, and deploy production machine learning and deep learning models using Python, PyTorch, TensorFlow, Scikit-learn, Pandas, and NumPy for large-scale financial and business datasets. Build automated ML pipelines covering data ingestion, preprocessing, feature engineering, model training, evaluation, deployment, and monitoring. Develop transformer-based and generative AI solutions, fine-tune and evaluate models for accuracy, performance, latency, and resource utilization. Create scalable inference services integrated into production applications via REST APIs and cloud services. Deploy and operate ML workloads using AWS, SageMaker, Docker, Kubernetes, and CI/CD pipelines to support scalable and reliable production AI services.

Production Support Engineer | AI/ML & Data Science at MPHASIS

October 1, 2019 - April 1, 2026

Developed Python- and SQL-based data science workflows for large-scale financial and transactional datasets supporting risk analytics, predictive modeling, and business decision-making. Performed exploratory data analysis, data profiling, cleansing, transformation, and feature engineering across complex datasets. Built predictive analytics models for fraud detection, risk scoring, transaction intelligence, and financial decision support. Developed and evaluated ML models using Python, Pandas, NumPy, and Scikit-learn for classification, regression, clustering, and model evaluation. Designed and maintained Jenkins CI/CD pipelines for Java microservices across PROD, UAT, QA, and SIT; supported deployment, testing, troubleshooting, and reliability; executed controlled production releases and performed root-cause analysis for production incidents in collaboration with engineering and infrastructure teams.