AI Engineer at Korn Ferry

Designed and developed AI agents to automate client work processes; implemented predictive models and data-driven capabilities; led end-to-end ML lifecycle from data processing to model deployment. Collaborated with cross-functional teams to translate requirements into scalable AI solutions.

AI Engineer at Experio

Led development of AI-driven solutions, streamlining automated work across multiple industries. Applied ML algorithms to improve decision-making, delivered data visualization dashboards for stakeholder insights, and integrated AI-powered tools to elevate productivity and business outcomes.

Architected machine learning models to predict customer trends and support strategic business initiatives. Managed full ML lifecycle from data preprocessing to model deployment and monitoring.

Led the creation of data-driven models to track customer interactions and optimize workflows. Collaborated with IT and business teams to translate requirements into actionable specifications, and designed automated reporting to inform stakeholders on industry trends.

Assisted in the development of company websites using HTML, CSS, and JavaScript; created attractive, user-friendly interfaces and contributed to backend services using Python, SQL, and API integration.

Senior ML Engineer at Mercor

Architected production ML inference pipelines for multimodal AI models, reduced latency by 40% through model quantization and optimized batching with Docker and Kubernetes. Deployed fine-tuned LLMs for content classification and retrieval using PyTorch and Transformers, achieving 95% accuracy on AB tests and supporting 500K daily user requests. Implemented RLHF-based retrieval augmented generation with FAISS vectors search, improving content discovery relevance by 32% and reducing cold-start recommendations. Designed CI/CD for ML pipelines using MLFlow and GitHub Actions, cutting deployment time from hours to 15 minutes and enabling reproducible experiments. Built real-time model monitoring dashboards with Prometheus and Grafana, detecting data drift within 5 minutes and maintaining 99.9% uptime. Optimized GPU utilization on AWS SageMaker and EKS, reducing inference cost per request by 28% while increasing throughput by 3x for video processing pipelines. Integrated AI chat bot for inte

Senior Software Engineer (ML Platform) at Expero Systems

Engineered ML platform; built event-driven data pipelines with Kafka and Apache Airflow, processing 10 TB+ daily telemetry data and feeding real-time features to inference models. Designed and deployed RESTful APIs for model services using FastAPI and gRPC, handling 10,000+ requests per second with 99.99% uptime. Implemented CI/CD for ML pipelines with MLFlow and GitHub Actions, enabling reproducible experiments and reducing deployment time. Built real-time model monitoring dashboards with Prometheus and Grafana, detecting data drift within 5 minutes and maintaining 99.9% uptime. Optimized GPU utilization on AWS SageMaker and EKS, improving throughput and reducing costs. Integrated AI chatbots for internal knowledge retrieval and data-driven decision making.

Fraud Detection Engineer / ML Engineer at ING Bank Śląski

Built fraud detection pipeline using Python and XGBoost, processing 2M+ daily transactions with 99.7% fraud capture rate and 0.2% false positive rate. Designed real-time transaction scoring service with Redis caching and REST API, achieving 50 ms response time. Implemented feature engineering on Spark (PySpark), generating 500+ features for risk models and reducing training time by 70%. Created dashboards with Grafana and Elasticsearch to monitor fraud metrics and data drift. Automated batch and streaming pipelines with Kafka/Airflow.