Berk Gökden

AI/ML & Data Engineer | Multi-Agent Systems · RAG · Data Infrastructure

Professional Summary

Full-stack AI/ML & Data Engineer who builds and ships GenAI applications and production ML systems end-to-end, fast and cost-efficiently. Delivered multi-agent AI systems, RAG pipelines, and LLM-powered applications at Klarna (5,000+ employees), with experience across recommendation systems, NLP, and data infrastructure at Booking.com, ING, and DPG Media. Led engineering at Vamp.io (acquired by CircleCI) managing a 12-person team. Open-source contributor (llama.cpp sampler, vector search) with expertise in Python, PySpark, LangChain, Hugging Face, scikit-learn, and distributed systems.

Professional Experience

Senior AI Engineer
Klarna
Sep 2023 - Dec 2025
Amsterdam, Netherlands
  • Built AI platform serving 5,000+ employees with multiple agent systems: meeting intelligence (40% efficiency improvement), conversational agents with voice capabilities, automated feedback systems, and internal search infrastructure
  • Deployed GenAI applications using LangChain with OpenAI and Anthropic LLMs under enterprise agreements with custom RAG implementations
  • Conducted systematic evaluation of LLM performance across different models (OpenAI, Anthropic, Hugging Face models such as Llama, Mistral) and parameters, iterating on prompts, RAG configurations, and model selection to optimize for accuracy, latency, and cost
  • Fine-tuned LLMs and embedding models from Hugging Face for domain-specific terminology and internal knowledge bases
  • Implemented vector search using PostgreSQL+pgvector, FAISS, and Annoy for cost-effective semantic search
  • Created Slack integrations and workflow automation tools including project management functionality
  • Deployed multi-agent systems that saved teams 15+ hours per week through automated workflows
  • Technologies: Python, TypeScript, Go, LangChain, OpenAI, Anthropic, Hugging Face, RAG, PostgreSQL+pgvector, FAISS, Docker, AWS
Senior Software Engineer - Data
Booking.com
May 2023 - Sep 2023
Amsterdam, Netherlands
  • Supported cloud migration from on-premise to AWS, facilitating data quality during infrastructure modernization
  • Developed data validation services and pipelines using microservices architecture
  • Improved data quality through governance framework, achieving 99% pipeline reliability
  • Validated millions of booking records daily across large-scale data processing systems
  • Technologies: DBT, Apache Spark SQL, Snowflake, Hadoop, Java, Python, Argo, Kubernetes, AWS
Senior Data Engineer
ING
Jul 2022 - Apr 2023
Amsterdam, Netherlands
  • Automated environmental sustainability data processing for ING Wholesale Banking, reducing processing time from weeks to hours
  • Built reliable daily pipeline tracking sustainability metrics for hundreds of companies used in credit score calculations, replacing manual Excel workflows
  • Developed framework and tools to help data engineers build production pipelines faster
  • Solved complex entity resolution challenges tracking company histories through mergers, closures, and restructuring
  • Technologies: Python, Apache Spark, PySpark, Kedro, Docker, Airflow, Kubernetes (OpenShift)
Big Data Engineer / ML Engineer
VodafoneZiggo
Sep 2021 - Feb 2022
Utrecht, Netherlands
  • Built predictive ML models to detect TV/internet box failures before they occurred, analyzing heat patterns and device telemetry
  • Automated proactive customer support by triggering service calls when boxes showed failure patterns, reducing box-related complaints by over 70%
  • Developed forecasting models to predict volume of failing boxes for capacity planning and inventory management
  • Delivered ML pipelines to production in collaboration with data scientists
  • Technologies: AWS (S3, EMR, Glue, Athena, DynamoDB, Lambda), Python
Machine Learning Engineer
DPG Media Netherlands
Sep 2020 - Aug 2021
Amsterdam, Netherlands
  • Built search re-ranking system for DPG Media magazine app using user history while avoiding filter bubbles
  • Developed notification optimization models tracking user engagement patterns to improve message interactions
  • Built user data pipeline merging clickstream data from multiple websites and apps across DPG Media acquisitions to create unified user profiles for ad targeting
  • Implemented ML models including classification, clustering, and decision trees for user segmentation, personalization, and content recommendations
  • Won company hackathon by building vector-based recommendation system using Universal Sentence Encoder for article enrichment and fast search, first transformer-based system deployed at DPG Media
  • Developed streaming applications using Apache Kafka (AWS MSK) and Spark Streaming for real-time data processing
  • Technologies: Python, scikit-learn, pandas, numpy, Apache Kafka, Spark, AWS (S3, DynamoDB, EKS), Airflow, MLFlow, FastAPI, Flask, Terraform, Universal Sentence Encoder
Senior Software Engineer
Caspar AI
Mar 2020 - Sep 2020
Rotterdam, Netherlands
  • Built AI sensor system for elderly care facilities in US, monitoring falls, controlling lighting/heating, and alerting nurses
  • Set up on-premise Kubernetes clusters inside buildings for privacy compliance, ensuring no user data left facilities
  • Deployed deep learning models for image recognition on edge servers, processing data locally for security
  • Built data pipeline sending only operational metrics to cloud while keeping sensitive data on-premise
  • Technologies: Python, Kubernetes (Kubespray), TensorFlow Serving, Nginx, AWS (S3, EC2, MSK), Kafka
Engineering Lead
Vamp.io (acquired by CircleCI)
Oct 2017 - Mar 2020
Amsterdam, Netherlands
  • Led engineering team of 12 people building cloud-native AIOps platform for canary releasing and microservices deployment
  • Built distributed systems and container orchestration infrastructure on Kubernetes
  • Developed AI load prediction algorithm for Vamp Continuous Cloud Optimizer, optimizing CPU and memory usage and reducing infrastructure costs by over 90%
  • Company subsequently acquired by CircleCI
  • Technologies: Go, Kubernetes, Docker, microservices architecture, machine learning
Senior Software Engineer
Zoover / Weeronline
Sep 2016 - Sep 2017
Amsterdam, Netherlands
  • Rebuilt weather data ETL pipeline for Weeronline app/website, reducing radar image and rain prediction latency from 45 minutes to under 1 minute
  • Rapidly built fraud detection system using Apache Spark analyzing review patterns and user behavior to identify and flag fraudulent reviews on Zoover platform
  • Set up CI/CD pipelines with Kubernetes (GKE), CircleCI, and GitLab using Scala
Developer
SAP SE
Mar 2015 - Sep 2016
Istanbul / Waldorf, Germany
  • Developed SAP Vora in-memory query engine integrated with Apache Spark for Big Data analytics on Hadoop
  • Built Docker-based deployment system for running Spark clusters in cloud environments
  • Worked on database internals and cloud service integrations for SAP Vora
Software Engineer
T2 Software
Nov 2013 - Mar 2015
Ankara, Turkey
  • Developed full-stack solutions for major Turkish telecom operator handling 100M+ subscriber records
  • Built customer service systems including provider transfer functionality completing migrations in under 10 minutes
  • Built service-oriented architecture and improved backend performance
  • Negotiated with stakeholders to improve API design
  • Technologies: Java, JavaScript, Oracle SQL
Software Engineer
Aselsan
Sep 2011 - Nov 2013
Ankara, Turkey
  • Developed real-time simulation system for radar test laboratory testing missile guidance systems
  • Built flight scenario simulator commanding radar hardware while logging and visualizing test results
  • Implemented distributed architecture using multi-threading and reflective memory in C/C++ on Linux

Open Source Contributions & Projects

veri - Vector Search in Go
github.com/bgokden/veri

Vector search engine built in Go for ML systems. High-throughput feature serving with low latency. 54+ GitHub stars.

llama-constrain - Constrained LLM Generation
github.com/bgokden/llama-constrain

Developed custom sampler in llama.cpp enabling strict constrained sampling in LLMs. Library for constrained text generation with Large Language Models for structured output using GGUF models.

Annoy - Vector Search Library (Contributor)
github.com/spotify/annoy

Contributor to Spotify's approximate nearest neighbors library for vector search. Built custom implementations for production use cases.

Technical Skills

AI/ML (High Priority)

  • GenAI Application Development
  • LLMs (Large Language Models)
  • RAG (Retrieval-Augmented Generation)
  • Multi-Agent Systems & Agentic AI
  • Conversational AI / Voice Agents
  • LangChain, Hugging Face
  • Model Fine-tuning (LLMs, Embeddings)
  • NLP & Recommendation Systems
  • scikit-learn, pandas, numpy
  • TensorFlow, PyTorch
  • llama.cpp, GGUF models

Languages

  • Python
  • Go
  • TypeScript
  • Scala
  • Java

Data & Vector Search

  • PostgreSQL + pgvector
  • FAISS
  • Annoy (contributor)
  • ETL/ELT Pipelines
  • Streaming Data Processing
  • Feature Stores
  • Data Warehousing
  • Analytics

Infrastructure & Architecture

  • Microservices Architecture
  • Service-Oriented Architecture
  • Kubernetes
  • Docker
  • CI/CD Pipelines
  • Distributed Systems
  • AWS
  • GCP

Education

Master of Science - Electronics & Electrical Engineering (Not Completed)
Bilkent University, Ankara
2010 - 2012

Focus: Machine Learning applied to signal/image/audio processing. Developed classification models using SVMs, including full ML pipeline: data collection, feature engineering, model development, testing, and validation. Technologies: MATLAB, Python, Support Vector Machines. Worked as Research and Teaching Assistant.

Bachelor of Science - Electronics & Electrical Engineering
Bilkent University, Ankara
2006 - 2010

Languages