Computer vision & perception

Computer Engineering graduate with experience in Software Quality Assurance, including manual testing and API testing. Worked on Laravel web applications and a C# desktop accounting system, and completed mobile development experience with React Native during internships. Growing skills in data analysis and test automation through coursework and self-directed projects.

LLM/MLOps Engineer (senior level) specializing in production RAG and multi-tenant AI system design with strong operational and schema-driven engineering focus. The strongest proven skill is building production-grade multi-tenant inference and RAG plumbing as evidenced by app/core/orchestrator.py, app/rag_engine/pinecone_client.py and FastAPI route handlers. Public code lacks custom deep-learning training loops, experiment tracking (W&B/MLflow) and demonstrated low-level GPU optimization implementations.

A machine learning practitioner focused on end-to-end supervised modeling and simple dashboards at a middle level, with practical strength in implementing sklearn pipelines and Streamlit apps. The strongest proven skill is building and packaging predictive pipelines as evidenced by the ColumnTransformer + Pipeline pattern, stratified train/test split and joblib model export in train.py. The work lacks robust validation, tests, reproducibility tooling and explicit fairness or regulatory treatment for production loan decisioning.

Generalist developer at a junior level focusing on web application development and basic NLP/transformers demonstrations. The strongest proven skill is building Django CRUD web applications as shown by implemented settings, views and forms code. Not evidenced are custom model training, experiment tracking, production ML serving, or performance optimization.

iOS engineer at a Middle level specializing in Swift and practical app features such as MVVM and networking. The strongest proven skill is modern async networking and pagination as shown by Pleny_Task/Pleny_Task/Repository/NetworkManager.swift and Pleny_Task/Pleny_Task/Views/Tabs/Posts/PostsViewModel.swift. There is limited evidence of offline sync, permission flows, performance measurement or release automation in public code.

Real-time pose-detection and applied ML developer (Middle level) focusing on Streamlit-based computer vision apps with modular landmark-based detectors. The strongest proven skill is integrating a MediaPipe pose landmarker into a real-time processing loop and building custom landmark heuristics for exercise metrics, as shown in services/vision/exercise_video_processor.py and detectors/biceps_curl.py. There is limited evidence of custom model training pipelines, experiment tracking, production MLOps, or automated test coverage in public code.

Senior software engineer and architect with 20+ years of experience building and supporting enterprise applications, distributed backends, and automated control system integrations. Experienced in C# and SQL performance tuning, Git-based SDLC, and enterprise integrations including Salesforce Commerce/Service Cloud. Hands-on background includes JavaScript and computer vision work with OpenCV.

Frontend UI engineer (middle level) focused on polished component work and visual design tokens. The strongest proven skill is building UI primitives and local state patterns, exemplified by the custom global toast system in src/hooks/use-toast.ts and a consistent tokenized theme in src/index.css and tailwind.config.ts. There is limited evidence of formal testing, large-scale architecture decisions, advanced server-state handling or explicit accessibility implementations in public code.

Backend-focused developer (middle level) with a practical strength in building small-to-medium JVM-based data-backed applications. The strongest proven skill is database-driven application wiring and JDBC-based DAO implementation as shown in StudySync-Pro/src/main/java/com/studyplatform/dao/StudyPlanDAO.java which includes table creation, prepared statements, generated keys handling and transaction rollback. There is limited evidence of production-grade API versioning, auth flows, formal migration chains, caches, or distributed systems design in public code.

A backend-focused Java API engineer with production-style microservices experience at a senior-adjacent level and a strength for building REST APIs with transactional, security and realtime concerns. The strongest proven skill is building backend service logic and integrations, evidenced by ExecutionService (local/Judge0 execution, timeouts and cleanup) and multiple domain services with tests such as SubmitMusicRequestService and PlayerPlaybackService. The public code does not show operational infra like deployment manifests, secret management, measured performance tuning or long-lived migration histories.

Medical imaging ML engineer (senior-level) focusing on 2D-3D X-ray registration, learned pose estimation, segmentation and related CV tooling. The strongest proven skill is building and evaluating model-based and classical registration workflows, grounded in artifacts such as src/registration/pose_cnn.py and src/registration/compare_classical_vs_learned.py. Public code shows limited MLOps productionization and minimal formal experiment tracking, and many infrastructure/serving files were marked as boilerplate rather than original work.

Software engineer with hands-on experience from internships in Python, SQL, and REST API development, validation, debugging, and root-cause analysis. Built automation for repetitive data/ETL validations and created AI-assisted RAG workflows, alongside test and deployment work using Docker and AWS services.

Computer Science graduate focused on AI applications, robotics software concepts, and junior software development. Built independent portfolio projects using React and TypeScript on the frontend with Material UI, and FastAPI with PostgreSQL on the backend, including exploration of RAG-based AI document assistant components. Has foundational study knowledge of ROS 2 and Gazebo concepts alongside machine learning and deep learning basics.

LLM-enabled full-stack engineer (middle level) focused on building pragmatic agentic systems and ML-enabled tools with an emphasis on integrations and end-to-end delivery. The strongest proven skill is integrating LLMs and content pipelines into a reliable product flow, demonstrated by the OllamaAgent and the FastAPI-based LinkedIn post agent (Postagent/src/linkedin_agent/ai/ollama_agent.py and Postagent/src/linkedin_agent/main.py). There is limited evidence of deep research work, production-grade MLOps (model versioning, profiling), or clinical-grade validation for health-related models.

Backend Python engineer (mid-level) focused on data profiling and ML pipelines with practical integrations to LLM agents. The strongest proven skill is building robust dataset profiling and analytics logic as implemented in app/services/profiler.py together with thorough unit tests in backend/tests/test_profiler_analytics.py. Production-grade concerns such as DB migrations, multi-service orchestration, comprehensive auth and runtime observability are not evidenced in the public code.

Backend Node.js developer (approx Middle level) who builds small REST APIs with authentication and CRUD functionality. The strongest proven skill is implementing JWT-protected user registration and login plus note CRUD, evidenced by controllers/authController.js and controllers/noteController.js. There is limited evidence of schema migration practice, automated tests, performance tuning, or production observability in the public code.

Backend-focused Python engineer (middle-level) with a clear strength in designing and testing domain logic for financial features. The strongest proven skill is precise EMI and amortization logic implemented and unit-tested in backend/services/emi_service.py and backend/tests/test_emi.py. There is limited evidence of production-grade security, secret management, resilience patterns and large-scale system design in public code.

Machine learning engineer with 5+ years of hands-on work across NLP, computer vision, LLM-related systems, intelligent document processing, and explainable AI. Focused on MLOps and productionization of ML models, including model training, evaluation, and deployment-oriented workflows. Built multiple R&D-to-PoC systems and ML-backed services using modern ML tooling.

Backend-focused generalist at a middle level specializing in pragmatic Node.js API and data-layer design. The strongest proven skill is server and database engineering shown by server/db.js which defines schema, migrations, indexes and a dbHelper wrapper. There is little to no public evidence of game-engine work, graphics or physics engineering, deterministic simulation, profiler-driven performance tuning, or test/CI coverage.

AI/ML Engineer and Technical Lead at HP Inc. with 5 years of experience and a PhD in Applied Computing. I focus on building enterprise agentic and generative AI systems, including persistent agents with RAG, memory/context management, tool use, and human-in-the-loop quality gates. I also develop reliable evaluation and observability pipelines and work on efficient and edge AI techniques such as distillation and quantization.