AI/ML Engineer - End-to-End Models & MLOps Expert

SAI KRISHNA

Tel: +1-561-***-**** Email: *******************@*****.***

PROFESSIONAL SUMMARY

Results-oriented AI/ML Engineer with 3 years of experience designing, developing, and deploying scalable machine learning, deep learning, and NLP solutions across BFSI, telecom, and insurance industries. Expertise in end-to-end ML lifecycle including data engineering, model development, MLOps automation, and cloud deployment. Proficient in Python, TensorFlow, PyTorch, Apache Spark, and modern data pipelines using Kafka and Airflow. Skilled in building production-grade AI systems for fraud detection, credit risk scoring, and predictive analytics that drive accuracy, efficiency, and real-time decision-making. Experienced in explainable AI, model monitoring, and compliance-driven AI systems. Strong collaborator with a track record of mentoring teams, aligning AI initiatives with business goals, and delivering results in Agile environments. TECHNICAL SKILLS

Programming & Tools: Python, SQL, Java, Bash, Git, GitHub, OOP, Data Structures & Algorithms Machine Learning & Deep Learning: Supervised/Unsupervised Learning, Neural Networks, CNNs, RNNs, Transformers, Recommendation Systems, Time Series Forecasting, Anomaly Detection Frameworks & Libraries: TensorFlow, PyTorch, Scikit-learn, XGBoost, LightGBM, Pandas, NumPy, Hugging Face, OpenCV Natural Language Processing: BERT, Text Classification, NER, Sentiment Analysis, Text Preprocessing Data Engineering: Apache Spark, Kafka, Airflow, dbt, ETL Pipelines, Delta Lake, Snowflake, Redshift MLOps & Deployment: Docker, Kubernetes, MLflow, GitHub Actions, CI/CD, REST APIs (FastAPI, Flask), Model Monitoring, A/B Testing

Cloud Platforms: AWS (SageMaker, S3, EC2, Lambda, Glue), Azure ML Studio, GCP Vertex AI Visualization & BI: Power BI, Tableau, Matplotlib, Seaborn, Plotly Databases: PostgreSQL, MySQL, MongoDB, DynamoDB, Parquet Mathematics & Statistics: Probability, Linear Algebra, Hypothesis Testing, Bayesian Inference, Statistical Modeling PROFESSIONAL EXPERIENCE

Kemp Technologies – AI/ML Engineer Apr 2025 – Present

• Developed and deployed fraud detection systems using XGBoost and LSTM, cutting false positives by 32% in claims processing.

• Built scalable data pipelines with PySpark and Kafka, handling over 100M daily transactions with low latency.

• Automated ML retraining workflows using Airflow and MLflow, enabling continuous model deployment with zero downtime.

• Designed NLP systems using Hugging Face BERT, reducing underwriting document review time by 40%.

• Implemented explainable AI using SHAP and LIME for transparent business decision-making and compliance readiness.

• Deployed containerized ML APIs with Docker, Kubernetes, and FastAPI, supporting 24/7 global insurance operations.

• Optimized Snowflake and Delta Lake pipelines, improving data query performance by 38%.

• Built Grafana and Power BI dashboards for real-time model performance monitoring and KPIs.

• Conducted A/B testing to fine-tune production models, achieving 18% improvement in risk assessment accuracy.

• Mentored junior engineers in MLOps, improving team adoption of automated AI workflows.

• Collaborated with compliance and audit teams to ensure transparent, audit-ready AI implementations.

• Integrated real-time model feedback loops using Kafka Streams and MLflow metrics, reducing model drift incidents by 28%.

• Architected RESTful microservices for AI APIs, cutting average response time to under 200ms across cloud regions.

• Implemented data versioning strategy using DVC and Git LFS to maintain reproducibility across 15+ model iterations. Capri Global – Machine Learning Engineer Aug 2021 – Sept 2023

• Engineered credit risk models using XGBoost and Random Forests, increasing approval accuracy by 22%.

• Created NLP pipelines with spaCy and BERT for loan document automation, reducing manual review effort by 65%.

• Optimized TensorFlow GPU workflows, reducing model training cycles by 45%.

• Automated ETL and data processing workflows using Airflow and Spark, processing over 5TB of financial data monthly.

• Deployed and monitored models on AWS SageMaker, achieving 30% faster inference performance.

• Built explainable credit risk dashboards using SHAP for interpretable model outputs.

• Designed and executed A/B tests to enhance loan scoring models, improving conversion rates by 18%.

• Developed recommendation systems for financial product upselling, driving 20% increase in customer adoption.

• Implemented CI/CD pipelines with GitHub Actions and MLflow to streamline deployment and rollback.

• Ensured compliance with RBI and international AI governance frameworks.

• Delivered ML projects on schedule under Agile and Scrum methodologies.

• Built real-time data ingestion pipeline using Kafka and AWS Lambda, enabling instant credit scoring decisions.

• Leveraged dbt and Delta Lake for data lineage tracking, enhancing governance and audit traceability. EDUCATION

Master of Science in Information Technology

Atlantis University

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