All Episodes

AI Platform: Memory, Tools, Guardrails, Observability, Shipping a Production Agent - Dewang Sultania

Building an AI Platform: SDK Design, Model Routing, Vector Search & Evals - Suhas Suresha

Decoding the Open Lakehouse - Sahil Walia

How AI Agents are Reshaping Modern Work - Philip Christos

Running a Company on a Multi Agent Dispatch System - Paul Domanski

The Data Consultant Playbook From Code to Business Impact - Tony Zeljkovic and Juan Manuel Perafan

Engineering AI-Powered Data Products - Radovan Bacovic

Engineering Your Own AI Assistant - Paul Iusztin

Thriving in the AI Era with Human Skills - Maryam Ramezani-Bartsch

Building a Career in AI From Real Estate to AI Engineering - Gustaf Gyllensporre

How to Build AI that actually Ships in Production - Aleksandr Kim

AI Adoption in Enterprise Beyond Writing Code - Ivan Bilan

Applied AI 2026 Berlin Conference Interview

From GenAI Pilots to Production - Nikita Kozodoi

From Notebook to Production: Building End-to-End AI Systems - Mariano Semelman

Data Makers Fest 2026 Conference Interviews

Competitions: Beyond the Kaggle Leaderboard - Tatiana Habruseva

PyConDE 2026 Conference Interviews

Starting a Data Conference: The Data Makers Fest Story - Leonid Kholkine

Understanding the AI Engineer Role - Nasser Qadri

Data Engineer Career in 2026: Roles, Specializations, and What Companies Look for - Slawomir Tulski

Inside the AI Engineer Role: Tools, Skills, and Career Path - Ruslan Shchuchkin

How to Become an AI Engineer After a Career Break - Revathy Ramalingam

The Future of AI Agents - Aditya Gautam

Foundations of Analytics Engineer Role: Skills, Scope, and Modern Practices - Juan Manuel Perafan

AI Engineering: Skill Stack, Agents, LLMOps, and How to Ship AI Products - Paul Iusztin

Applying ML: An Ongoing Personal Journey

Building Pet Health Tech: ML, Sensors, and Dog Behavior Data

From Full-Time Mom to Head of Data and Cloud - Xia He-Bleinagel

From Black-Box Systems to Augmented Decision-Making - Anusha Akkina

Qdrant 2025 Conference Interviews

How to Build and Evaluate AI systems in the Age of LLMs - Hugo Bowne-Anderson

From Biotechnology to Bioinformatics Software - Sebastian Ayala Ruano

Lessons from Applied AI: Tesla, Waymo, and Beyond - Aishwarya Jadhav

Building reliable AI products in the era of Gen AI and Agents - Ranjitha Kulkarni

From Theme Parks to Tesla: Building Data Products That Work

From Semiconductors to Machine Learning: A Career in Data and Teaching

Lessons from Two Decades of AI - Micheal Lanham

Berlin PyData 2025 Conference Interviews

From Astronomy to Applied ML - Daniel Egbo

Berlin Buzzwords 2025 Conference Interviews

From Medicine to Machine Learning: How Public Learning Turned into a Career - Pastor Soto

How to Rebuild Data Trust? Mindful Data Strategy and Maintenance vs Innovation - Lior Barak

From Simulations to Freelance Data Engineering: Orell's Journey Out of Academia and Into Consulting - Orell Garten

Can You Quit Your Job and Still Succeed as a Data Freelancer?

From Hackathons to Developer Advocacy - Will Russel

Build a Strong Career in Data - Lavanya Gupta

From Supply Chain Management to Digital Warehousing and FinOps - Eddy Zulkifly

Data Intensive AI - Bartosz Mikulski

MLOps in Corporations and Startups - Nemanja Radojkovic

Trends in Data Engineering – Adrian Brudaru

Competitive Machine Leaning And Teaching – Alexander Guschin

Redefining AI Infrastructure: Open-Source, Chips, and the Future Beyond Kubernetes – Andrey Cheptsov

Linguistics and Fairness - Tamara Atanasoska

Career choices, transitions and promotions in and out of tech - Agita Jaunzeme

Career advice, learning, and featuring women in ML and AI - Isabella Bicalho

AI in Industry: Trust, Return on Investment and Future - Maria Sukhareva

Large Hadron Collider and Mentorship – Anastasia Karavdina

MLOps as a Team - Raphaël Hoogvliets

Using Data to Create Liveable Cities - Rachel Lim

DataTalks.Club 4th Anniversary AMA Podcast – Alexey Grigorev and Johanna Bayer

Human-Centered AI for Disordered Speech Recognition - Katarzyna Foremniak

DataOps, Observability, and The Cure for Data Team Blues - Christopher Bergh

Working as a Core Developer in the Scikit-Learn Universe - Guillaume Lemaître

Building a Domestic Risk Assessment Tool - Sabina Firtala

Berlin Buzzwords 2024

Community Building and Teaching in AI & Tech - Erum Afzal

Working in Open Source - Probabl.ai and sklearn - Vincent Warmerdam

AI for Ecology, Biodiversity, and Conservation - Tanya Berger-Wolf

Knowledge Graphs and LLMs Across Academia and Industry - Anahita Pakiman

Inclusive Data Leadership Coaching - Tereza Iofciu

Building Production Search Systems - Daniel Svonava

Building Machine Learning Products - Reem Mahmoud

Make an Impact Through Volunteering Open Source Work - Sara EL-ATEIF

Accelerating The Job Hunt for The Perfect Job in Tech - Sarah Mestiri

Machine Learning Engineering in Finance - Nemanja Radojkovic

Stock Market Analysis with Python and Machine Learning - Ivan Brigida

Bayesian Modeling and Probabilistic Programming - Rob Zinkov

Navigating Challenges and Innovations in Search Technologies - Atita Arora

The Entrepreneurship Journey: From Freelancing to Starting a Company - Adrian Brudaru

Become a Data Freelancer - Dimitri Visnadi

AI for Digital Health - Maria Bruckert

Cracking the Code: Machine Learning Made Understandable - Christoph Molnar

The Unwritten Rules for Success in Machine Learning - Jack Blandin

From a Research Scientist at Amazon to a Machine learning/AI Consultant - Verena Webber

From Marketing to Product Owner in Search - Lera Kaimashnіkova

Collaborative Data Science in Business - Ioannis Mesionis

Bridging Data Science and Healthcare - Eleni Stamatelou

DataTalks.Club Anniversary Interview - Alexey Grigorev, Johanna Bayer

Data Engineering for Fraud Prevention - Angela Ramirez

From Data Manager to Data Architect - Loïc Magnien

Pragmatic and Standardized MLOps - Maria Vechtomova

Democratizing Causality - Aleksander Molak

Mastering Data Engineering as a Remote Worker - José María Sánchez Salas

The Good, the Bad and the Ugly of GPT - Sandra Kublik

LLMs for Everyone - Meryem Arik

Investing in Open-Source Data Tools - Bela Wiertz

Why Machine Learning Design is Broken - Valerii Babushkin

Interpretable AI and ML - Polina Mosolova

From Scratch to Success: Building an MLOps Team and ML Platform - Simon Stiebellehner