{
  "$schema": "https://jsonresume.org/schema/",
  "basics": {
    "name": "Nikolas Bakalis",
    "label": "Senior Software Engineer, Applied AI & Backend",
    "email": "me@nikolasbakalis.com",
    "url": "https://nikolasbakalis.com/",
    "image": "https://nikolasbakalis.com/profile/2026-02-16-nikolas-bakalis-headshot.jpg",
    "summary": "I build production AI, ML, and backend systems end-to-end, from early product development through scaled production operations, covering problem framing, evaluation, deployment, monitoring, and business impact.",
    "location": {
      "city": "New York",
      "region": "NY",
      "countryCode": "US"
    },
    "profiles": [
      {
        "network": "LinkedIn",
        "username": "nikolas-bakalis",
        "url": "https://www.linkedin.com/in/nikolas-bakalis/"
      },
      {
        "network": "GitHub",
        "username": "NikosBakalis",
        "url": "https://github.com/NikosBakalis"
      }
    ]
  },
  "work": [
    {
      "name": "Channel Factory",
      "position": "Senior Software Engineer, Applied AI & Backend",
      "startDate": "2024-11",
      "summary": "Builds production AI, data, and backend systems for advertising workflows across tens of millions of YouTube channels and billions of videos. Delivers early-stage MVPs and scaled production systems with measurable revenue and operational impact. Works with foundation models, RAG, MCP, data lakehouse architecture, and service contracts.",
      "highlights": [
        "Builds production AI, data, and backend systems for advertising workflows across tens of millions of YouTube channels and billions of videos.",
        "Delivers early-stage MVPs and scaled production systems with measurable revenue and operational impact.",
        "Works with foundation models, RAG, MCP, data lakehouse architecture, and service contracts."
      ]
    },
    {
      "name": "ACERTUS",
      "position": "Software Engineer, ML Engineering & Full Stack",
      "startDate": "2022-05",
      "endDate": "2024-11",
      "summary": "Built production ML for ETA, delay, and fraud prediction in logistics workflows. Owned cloud deployments with Python, AWS, Docker, and production monitoring.",
      "highlights": [
        "Built production ML for ETA, delay, and fraud prediction in logistics workflows.",
        "Owned cloud deployments with Python, AWS, Docker, and production monitoring."
      ]
    },
    {
      "name": "Vivpro",
      "position": "Full Stack Engineer, ML Engineering",
      "startDate": "2021-06",
      "endDate": "2022-05",
      "summary": "Built ML and full-stack systems for regulatory and clinical-trial intelligence workflows. Worked on natural-language interfaces before commercial LLM tooling became mainstream.",
      "highlights": [
        "Built ML and full-stack systems for regulatory and clinical-trial intelligence workflows.",
        "Worked on natural-language interfaces before commercial LLM tooling became mainstream."
      ]
    }
  ],
  "education": [
    {
      "institution": "Anglia Ruskin University",
      "area": "Artificial Intelligence and Big Data",
      "studyType": "M.S."
    },
    {
      "institution": "University of Patras",
      "area": "Computer Engineering",
      "studyType": "Integrated B.Eng. and M.Eng."
    }
  ],
  "awards": [
    {
      "title": "Product/Tech Star of the Year",
      "date": "2026",
      "awarder": "Channel Factory"
    }
  ],
  "skills": [
    {
      "name": "Core skill areas",
      "keywords": [
        "Production AI systems",
        "Applied machine learning",
        "Backend engineering",
        "AWS data platforms",
        "RAG and agentic workflows",
        "MCP integrations",
        "LLM evaluation",
        "NLP and language detection",
        "Computer vision",
        "Adversarial machine learning",
        "Database serving architecture",
        "API performance benchmarking",
        "Data lakehouse architecture",
        "Model monitoring and evaluation"
      ]
    },
    {
      "name": "Selected technologies",
      "keywords": [
        "AWS",
        "AWS Bedrock",
        "AWS Glue",
        "S3",
        "Athena",
        "RDS",
        "PostgreSQL",
        "StarRocks",
        "OpenSearch",
        "Iceberg",
        "S3 Tables",
        "Redis",
        "Python",
        "TypeScript",
        "Go",
        "Node.js",
        "Bun",
        "Docker",
        "FastAPI",
        "Django",
        "Fastify",
        "Fiber",
        "BlackSheep",
        "Celery",
        "TensorFlow/Keras",
        "ResNet50",
        "Computer vision",
        "Adversarial ML",
        "RAG",
        "MCP",
        "LLMs",
        "NLP",
        "XLM-RoBERTa",
        "FastText",
        "Language detection",
        "Translation evaluation",
        "COMET-QE",
        "BERTScore",
        "LLM evaluation",
        "Model monitoring",
        "Backend performance"
      ]
    }
  ],
  "projects": [
    {
      "name": "Translation Model Benchmark for Multilingual Video Transcripts",
      "description": "A multilingual benchmark comparing Google Translate, DeepL, and Llama Maverick 4 on noisy video transcript data across 15 languages.",
      "url": "https://nikolasbakalis.com/work/translation-model-benchmark-video-transcripts/",
      "startDate": "2026-05-25",
      "keywords": [
        "Translation",
        "LLMs",
        "Evaluation",
        "Transcripts",
        "Translation",
        "Python",
        "Google Translate",
        "DeepL",
        "Llama Maverick 4",
        "Together AI",
        "COMET-QE",
        "BLEU",
        "BERTScore"
      ],
      "roles": [
        "Benchmark"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Benchmark"
    },
    {
      "name": "RDS vs StarRocks 20M Serving and Aggregation Benchmark",
      "description": "A 20 million row benchmark comparing RDS/Postgres serving tables with StarRocks OLAP tables and async materialized views.",
      "url": "https://nikolasbakalis.com/work/rds-starrocks-serving-aggregation-20m-benchmark/",
      "startDate": "2026-05-22",
      "keywords": [
        "RDS",
        "StarRocks",
        "OLAP",
        "Benchmark",
        "Data Systems",
        "AWS",
        "RDS/PostgreSQL",
        "StarRocks",
        "Iceberg",
        "S3 Tables",
        "Materialized Views",
        "Python"
      ],
      "roles": [
        "Benchmark"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Benchmark"
    },
    {
      "name": "Materialized View API Serving Benchmark",
      "description": "An API-level comparison of denormalized RDS tables and StarRocks async materialized views across 100k, 1m, and 10m row scales.",
      "url": "https://nikolasbakalis.com/work/materialized-view-api-serving-benchmark/",
      "startDate": "2026-05-21",
      "keywords": [
        "RDS",
        "StarRocks",
        "API",
        "Materialized views",
        "Data Systems",
        "PostgreSQL",
        "StarRocks",
        "Iceberg",
        "S3 Tables",
        "Materialized Views",
        "REST APIs",
        "Docker"
      ],
      "roles": [
        "Benchmark"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Benchmark"
    },
    {
      "name": "IAB 3.0 Content Classifier Training Report",
      "description": "A training report for an in-house hierarchical IAB 3.0 content classifier built to replace external classification dependencies.",
      "url": "https://nikolasbakalis.com/work/iab-3-content-classifier-training-report/",
      "startDate": "2026-03-20",
      "keywords": [
        "IAB 3.0",
        "Classification",
        "NLP",
        "Training",
        "ML/NLP",
        "Python",
        "NLP",
        "IAB 3.0",
        "Hierarchical Classification",
        "Model Evaluation",
        "Taxonomy Modeling"
      ],
      "roles": [
        "Technical Note"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Technical Note"
    },
    {
      "name": "API Framework Benchmark for Data-Intensive Services",
      "description": "A benchmark of API frameworks and datastore access patterns for data-intensive services spanning PostgreSQL, StarRocks, and OpenSearch.",
      "url": "https://nikolasbakalis.com/work/api-framework-benchmark-data-intensive-services/",
      "startDate": "2026-03-16",
      "keywords": [
        "API",
        "Backend",
        "PostgreSQL",
        "OpenSearch",
        "Backend",
        "Go",
        "Python",
        "Node.js",
        "Bun",
        "Docker",
        "PostgreSQL",
        "StarRocks",
        "OpenSearch"
      ],
      "roles": [
        "Benchmark"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Benchmark"
    },
    {
      "name": "IAB 3.0 Classification and Language Detection Pipeline Proposal",
      "description": "A project proposal for replacing external classification APIs with in-house IAB 3.0 classification and language detection pipelines at media-corpus scale.",
      "url": "https://nikolasbakalis.com/work/iab-3-classification-language-detection-pipeline-proposal/",
      "startDate": "2026-03-01",
      "keywords": [
        "IAB 3.0",
        "Language detection",
        "Classification",
        "Pipeline",
        "ML/NLP",
        "AWS Glue",
        "Iceberg",
        "S3",
        "Celery",
        "GCLD3",
        "FastText",
        "XLM-RoBERTa",
        "IAB 3.0"
      ],
      "roles": [
        "Proposal"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Proposal"
    },
    {
      "name": "Adversarial Robustness in Medical Image Classification",
      "description": "Master's thesis work evaluating adversarial attacks and defensive training strategies for cervical cancer screening image classification models.",
      "url": "https://nikolasbakalis.com/work/adversarial-ml-medical-image-classification/",
      "startDate": "2023-09-15",
      "keywords": [
        "Adversarial ML",
        "Medical imaging",
        "ResNet50",
        "Model robustness",
        "Adversarial ML",
        "Python",
        "TensorFlow/Keras",
        "ResNet50",
        "Adversarial ML",
        "FGSM",
        "BIM",
        "Gaussian noise",
        "Medical imaging"
      ],
      "roles": [
        "Thesis"
      ],
      "entity": "Nikolas Bakalis",
      "type": "Thesis"
    }
  ]
}