Free Lesson
How to Become a Machine Learning Engineer in 2026
30 min
Feb 16, 2026 5:00 PM
Virtual (Zoom)
In this video
What you'll learn
A realistic view of the machine learning roles in 2026
Understand how the role is evolving beyond model training into systems, deployment, and reliability.
The core skills ML engineers actually need
Learn which fundamentals in data, modeling, infrastructure, and software engineering matter most.
How ML engineers work with data, models, production systems
See how experiments become deployed, monitored ML systems.
Where to focus when learning or reskilling
Prioritize skills that translate to real-world impact.
How to move from experimentation to production ML
Understand what differentiates notebooks from production-ready ML systems.
Why this topic matters
The ML engineer role is often misunderstood as model tuning alone. In reality, it’s about building reliable systems around models. This session focuses on what the job actually looks like in 2026, helping learners invest in skills that matter long term.
You'll learn from

Aki Wijesundara, PhD
AI Founder | Google AI Accelerator Alum

Manu Jayawardana
AI Advisor | Co-Founder & CEO at Krybe | Co-Founder of Snapdrum
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