Solves complex problems and help stakeholders make data- driven decisions by leveraging quantitative methods such as machine learning It often involves synthesizing large volume of information and extracting signals from data in a programmatic way Roles Responsibility RESPONSIBILITIES Technical Strategy Leadership Define and lead the technical roadmap for machine learning deep learning LLMs and AI initiatives Architect end-to-end ML pipelines including data ingestion feature engineering model training evaluation deployment and monitoring Mentor junior data scientists and provide technical guidance across modeling experimentation and best coding practices Establish standards for model governance explainability reproducibility and documentation Machine Learning Predictive Modeling Oversee the design development and deployment of supervised and unsupervised learning models including classification regression forecasting clustering and anomaly detection Implement feature engineering model optimization hyperparameter tuning and MLOps practices for scalable production systems Conduct A B experiments evaluate model performance and ensure robustness fairness and compliance Lead initiatives involving Large Language Models LLMs Generative AI and Agentic AI to enable content creation workflow automation and autonomous decision-making Fine-tune evaluate and deploy foundational models and multimodal AI architectures Build conversational agents recommendation engines and knowledge reasoning systems leveraging transformer-based models Deep Learning Computer Vision Drive research and application of ANNs RNNs LSTMs Transformers Computer Vision and Transfer Learning techniques for sequential image and multimodal data Develop and optimize architectures for tasks such as object detection segmentation OCR time-series prediction and embeddings Deploy deep learning models on cloud environments or edge devices using optimized runtimes TensorRT ONNX etc Data Engineering MLOps Collaborate with data engineering teams to design scalable data pipelines and cloud architectures AWS Azure GCP Implement CI CD pipelines for ML model monitoring systems and automated retraining workflows Ensure data quality governance and compliance with security and privacy standards Desired Candidate Profile EDUCATION KNOWLEDGE Master s in Computer Science Data Science Machine Learning Statistics or related field QUALIFICATIONS EXPERIENCE 6 years of experience in machine learning deep learning natural language processing or applied AI Robust proficiency in Python ML DL frameworks TensorFlow PyTorch Scikit-learn and data pipelines Experience deploying ML models to production environments Docker Kubernetes MLflow SageMaker Vertex AI etc Strong understanding of statistical modeling optimization and experimental design Experience with LLMs vector databases RAG pipelines and model fine-tuning Hands-on experience with Computer Vision transformers sequence modeling and multimodal architectures Familiarity with MLOps distributed training and big-data ecosystems Spark Databricks Snowflake Strong communication leadership and cross-team collaboration skills MOTIVATIONAL CULTURAL FIT Demonstrate Customer Focus Communicate Effectively Competencies Values Integrity Accountability Inclusion Innovation Teamwork ABOUT TE CONNECTIVITY TE Connectivity plc NYSE TEL is a global industrial technology leader creating a safer sustainable productive and connected future As a trusted innovation partner our broad range of connectivity and sensor solutions enable the distribution of power signal and data to advance next-generation transportation energy networks automated factories data centers enabling artificial intelligence and more Our more than 90 000 employees including 10 000 engineers work alongside customers in approximately 130 countries In a world that is racing ahead TE ensures that EVERY CONNECTION COUNTS Learn more at www te com and on LinkedIn Facebook WeChat Instagram and X formerly Twitter WHAT TE CONNECTIVITY OFFERS We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority Competitive Salary Package Performance-Based Bonus Plans Health and Wellness Incentives Employee Stock Purchase Program Community Outreach Programs Charity Events Employee Resource Group IMPORTANT NOTICE REGARDING RECRUITMENT FRAUD TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process All legitimate job openings are posted exclusively on our official careers website at te com careers and all email communications from our recruitment team will come only from actual email addresses ending in te com If you receive any suspicious communications we strongly advise you not to engage or provide any personal information and to report the incident to your local authorities Across our global sites and business units we put together packages of benefits that are either supported by TE itself or provided by external service providers In principle the benefits offered can vary from site to site Job Locations Bangalore Karn taka 560076 India Posting City Bangalore Job Country India Travel Required None Requisition ID 146755 Workplace Type Hybrid External Careers Page Information Technology

📌 Sr. Data Scientist (Karnataka)
🏢 TE Connectivity
📍 Karnataka