3 information technology jobs found

Position: Lead Data Engineer Job Description: Job Title: Data Engineer with ML Exposure Role Summary Tech Lead with core experience in Data Engineering and have good understanding of Machine Learning. Build and operate scalable, reliable data pipelines on Azure. Develop batch and streaming ingestion, transform data using industry standard data analytics and AI platform (PySpark/SQL), ADF/Snowflake or equivalent, enforce data quality, and publish curated datasets for analytics and ML. Good understanding of supervised, unsupervised learning, model evaluation, and feature engineering Key Responsibilities Design, build, and maintain ETL/ELT pipelines in Azure Data Factory and equivalent tool across Bronze → Silver → Gold layers/Medallion Architecture. Implement Delta Lake best practices (ACID, schema evolution, MERGE/upsert, time travel, Z-ORDER). Write performant PySpark and SQL; tune jobs (partitioning, caching, join strategies). Create reusable...

Position: Solution Engineer II (AI/ML lead) Job Description: Principal Accountabilities Collaborate with teams to translate business requirements into technical specifications, system architecture, and ML pipelines. Drive end-to-end solution delivery — including data preparation, model development, optimization, validation, deployment, and continuous improvement. Provide technical guidance and mentorship to junior engineers and data scientists; review and refine their designs and code implementations. Develop reusable ML frameworks, model training workflows, and inference pipelines for rapid prototyping and deployment. Evaluate and integrate state-of-the-art AI/ML technologies to continuously improve model efficiency and system design. Respond to client RFQs and provide robust technical proposals and solution architectures. Partner cross-functionally with system engineers, embedded developers, and application teams for integrated AI system delivery. Job...

Position: AI ML Engineer Job Description: 2 to 5+ years of experience in understanding the problem statement, data handling/triage, selecting and improving neural network models using deep learning frameworks to solve business problems. Excellent hands-on Coding in Python (mandatory), C/C++ or Java. Experience in developing AI/ML/DL models by using transfer learning or from scratch. Reasonably good knowledge on leading deep learning frameworks like Tensorflow, PyTorch, ONNX, Keras and others. Working experience in computer vision models like Yolo, Mobilenet, Resnet etc. Good understanding and working knowledge of AI/ML/DL on Edge (for e.g. Nvidia Jetson family, Qualcomm, Intel, Rpi). Thorough understanding and experience of DL/AI/ML lifecycle - full neural network pipeline, starting from data collection to model building to experimental framework to data analytics. Developed/optimized various models in computing domain (Video, Statistics , Audio and others)....