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Senior AI/ML Engineer with 7+ years in AI, MLOps, and Full Stack Development
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Competencies
Extensive experience designing and deploying machine learning models and AI systems in production environments.
Proficient in building and maintaining automated ML pipelines, model deployment, and lifecycle management.
Skilled in developing end-to-end AI applications using React, Python, APIs, and cloud services.
Knowledgeable in designing prompts, fine-tuning models, and working with LLMs for natural language applications.
Experienced with cloud services, backend APIs, and scalable architectures supporting AI solutions.
Education
Summary
Experienced AI/ML professional specializing in developing and deploying advanced machine learning models, building robust MLOps pipelines, and creating full-stack AI applications to solve complex business challenges.
Key Achievements
- Architected scalable production AI/ML systems supporting financial workflows at Plaid.
- Designed and implemented enterprise MLOps infrastructure, streamlining model lifecycle management at EPAM Systems.
- Developed full-stack AI applications integrating machine learning, natural language processing, and scalable backend solutions.
- Built automated ML pipelines and optimized model deployment processes, enhancing efficiency and reliability.
Experience
Senior AI/ML Engineer
Architected and developed production AI/ML systems supporting financial intelligence workflows using Python, machine learning frameworks, cloud services, and scalable backend architectures.. Built LLM-powered applications integrating large language models, retrieval workflows, prompt engineering, and evaluation pipelines to improve intelligent automation capabilities.. Designed recommendation and personalization solutions using machine learning approaches, feature engineering, ranking strategies, and data-driven optimization.. Implemented MLOps workflows including model deployment, monitoring, versioning, experiment tracking, and automated evaluation pipelines.. Collaborated with product managers, data scientists, and engineering teams to define AI strategies and deliver reliable customer-facing solutions.
Senior MLOps Engineer
Designed and maintained enterprise MLOps infrastructure supporting machine learning model lifecycle management from development through production deployment.. Built automated ML pipelines using Python, Docker, Kubernetes, MLflow, Airflow, and cloud platforms to improve engineering efficiency and reliability.. Developed model monitoring and observability frameworks for tracking performance, data quality, drift detection, and operational health.. Implemented scalable data processing workflows using distributed computing technologies including Spark and cloud-based data platforms.. Partnered with data scientists and software engineers to productionize healthcare AI solutions while maintaining quality, security, and compliance standards.
Full Stack AI Engineer
Developed full-stack AI applications combining React, Python, backend APIs, databases, and machine learning services.. Built intelligent automation features using machine learning models, natural language processing, and data-driven decision systems.. Designed scalable backend services and APIs supporting high-performance financial applications and customer workflows.. Integrated cloud services and AI capabilities to improve application reliability, scalability, and user experience.. Collaborated with global engineering teams and business stakeholders to deliver end-to-end software solutions.
Full Stack Engineer
Developed scalable SaaS applications using modern frontend and backend technologies with focus on maintainability and performance.. Designed RESTful APIs and backend services supporting business workflows, integrations, and customer-facing features.. Implemented database solutions and application architectures to improve reliability and operational efficiency.. Collaborated with designers, product managers, and engineers to deliver features from requirements through deployment.. Improved software quality through testing, code reviews, and engineering best practices across development teams.
Backend Developer Intern
Developed backend components and API services supporting internal business applications.. Improved application functionality through debugging, database optimization, and software development practices.