# Chandra Sekhar > AI/ML Engineer @ Ford Credit | Google Cloud Platform, AI Location: Farmington, Michigan, United States Profile: https://flows.cv/chandrasekhar As an AI/ML Engineer at Ford Credit, I specialize in leveraging Google Cloud Platform (GCP) and machine learning to enhance fraud detection through innovative graph-based solutions. My experience includes designing end-to-end proof of concepts, implementing scalable feature engineering pipelines, and delivering production-ready models to improve fraud signal quality and interpretability. With a Master's in Data Science from the University of Michigan, I am passionate about applying cutting-edge AI and machine learning techniques to solve complex challenges. My goal is to contribute to impactful projects that drive business innovation and operational efficiency, while fostering collaboration and mentorship within technical teams. ## Work Experience ### AI/ML Engineer @ Ford Credit Jan 2025 – Present | Dearborn, MI • Designed and implemented an end-to-end fraud detection proof of concept (PoC) using knowledge graphs from structured financial data in GCP(VERTEX AI). • Developed graph-based feature engineering pipelines with NetworkX and GraphFrames for scalable processing. • Migrated the solution to distributed GraphFrames on GCP Dataproc clusters, enhancing high-volume graph analytics. • Delivered a production-ready PoC that improved fraud signal quality and model interpretability through graph topology. ### AI/ML Engineer @ CORtracker 360 Jan 2024 – Jan 2025 | Novi, MI • Spearheaded Symplore’s real estate ventures, driving profitable investment strategies and delivering a substantial revenue boost. • Implemented complete document classification, analysis, understanding, and extraction, as well as enrichment pipelines, developing multiple services using Prefect as Data workflow Orchestration • Engineered and fine-tuned LLMs using LoRA and quantization, enabling precise extraction of critical information from unstructured data along with RAG techniques and evaluation using RAGAS and custom frameworks • Deployed and integrated multiple highly scalable Async services to handle batch processing and real-time systems • Managed Data Science team and mentored junior data scientists towards best practices and proof of concepts ### Prompt Engineer @ Outlier Jan 2024 – Jan 2025 | Farmington, Michigan, United States • Developed and fine-tuned multimodal large language models (LLMs) using advanced prompt engineering techniques and RLHF. • Designed and optimized training datasets to improve model performance across various modalities. • Conducted thorough evaluations of AI-generated outputs to ensure factual accuracy and reduce hallucinations through feedback loops. ### Machine Learning Engineer @ Phablecare Jan 2020 – Jan 2022 | Bangalore Urban, Karnataka, India • Led ML team responsible for digitizing and automating biz operations using unstructured data at Phablecare. • Led Early-Stage chronic Hypertension Data Ingestion for Phablecare on a Peta Bytes scale. Data engineered some data to auto-label data for NER using weak supervision frameworks like Snorkel, skweak and maintained MLOps • Developed ML pipeline to extract disease-related entities from unstructured text data with coverage of 92% and accuracy of 95%, processing clinical documents worth over 5 Million USD. • Containerized and deployed all the ML services using AWS Kubernetes and built pipelines to automate flow ### Data Science Intern @ Perfios Jan 2019 – Jan 2020 | Bengaluru, Karnataka, India * Automated financial data processing and reduced execution time from hours to under 30 seconds * Built NLP models with 70% precision and limited dataset and developed active feedback loop with F1-score of 0.71 * Developed probabilistic annotations using BERT to minimize manual annotations and trained a SpaCy Custom NER model to process USD 10 million worth of financial transactions with an active retraining loop. * Developed an anomaly detection algorithm using PySpark with a Hive backend, processing 10,000 transactions per week, improving the productivity of the Syndicate Bank finance team by 70% through automation.. ## Education ### Masters in data science University of Michigan ### Bachelor of Technology - BTech in Electrical, Electronics and Communications Engineering Dayananda Sagar College of Engineering, BANGALORE ## Contact & Social - LinkedIn: https://linkedin.com/in/chandra5699 - GitHub: https://github.com/Chandu5699 --- Source: https://flows.cv/chandrasekhar JSON Resume: https://flows.cv/chandrasekhar/resume.json Last updated: 2026-04-18