Machine Learning Engineer III, ML Operations

Job Description

🏢Company: Expedia Group
📍Location: Bangalore, Karnataka, India 🇮🇳
💼Job Type: Full-Time, Regular
🏢Work Mode: Onsite/Hybrid
⏳Experience: 5+ Years
🎓Education: Bachelor’s/Master’s Degree in Computer Science or a related technical field
💰Expected Salary: ₹7 – ₹10 Lakhs Per Year 💸
📊Job Category: Information Technology, Engineering, Machine Learning, AI/ML, MLOps, Data Science, Software Engineering, Technology 🌐
🌐Website: Website
📞Contact: Contact us

🌟Your ML model isn’t finished when it works.

It’s finished when it survives production.

Millions of users.

Real-time decisions.

Constant data changes.

And systems that cannot afford to fail.

That’s the challenge Expedia Group is hiring for.

The company is looking for a Machine Learning Engineer III – ML Operations in Bengaluru to build, scale and operate production-grade machine learning systems.

This isn’t just an ML role.

It’s where machine learning meets software engineering, distributed systems and production reliability.

🌟About Expedia Group:
Expedia Group is a global travel technology company behind brands including Expedia, Hotels.com and Vrbo.

Its technology helps millions of travelers discover, book and experience travel around the world.

The company currently operates across multiple global locations, including Bengaluru, and its technology teams work on large-scale systems used by travelers worldwide.

💡About the Role:
As a Machine Learning Engineer III, you’ll work with the Meta/SEM Bidding Programs team.

Your mission?

Turn experimental data science workflows into reliable, scalable ML production systems.

You’ll work across:

🤖 Machine Learning
⚙️ Software Engineering
📊 Big Data
☁️ Cloud Infrastructure
🚀 MLOps
🧠 Generative AI & LLMs
📈 Production Monitoring

You’ll also mentor junior engineers and lead complex projects in a high-scale production environment.

📌Key Responsibilities:
📌 Build, refactor and test complex ML and software components

📌 Convert experimental data science workflows into production-ready pipelines

📌 Design large-scale ML and big-data applications

📌 Build systems for batch and streaming inference

📌 Train, evaluate and deploy machine learning models at scale

📌 Monitor production models for latency, throughput, quality and business KPIs

📌 Detect data drift and model drift

📌 Implement retraining, recalibration and architecture improvements

📌 Design production guardrails, thresholds, fallbacks and safe defaults

📌 Improve system observability and operational efficiency

📌 Optimize memory and compute utilization

📌 Apply AI tools throughout the software and ML engineering lifecycle

📌 Explore responsible applications of GenAI and LLM technologies

📌 Collaborate with engineers, data scientists and business stakeholders

📌 Mentor junior engineers and contribute to technical best practices

🎯Requirements:
🎯 5+ years of professional experience in end-to-end ML engineering

🎯 Experience building production ML pipelines

🎯 Strong experience with Spark or similar big-data frameworks

🎯 Proficiency with PyTorch and/or TensorFlow

🎯 Strong understanding of machine learning fundamentals

🎯 Experience with deep learning and big-data systems

🎯 Experience scaling ML models for production

🎯 Knowledge of MLOps, CI/CD, experiment tracking and model registries

🎯 Experience with model monitoring and observability

🎯 Understanding of distributed systems

🎯 Familiarity with secure data access and governance

🎯 Experience with hybrid/cloud environments

🎯 Knowledge of generative AI and LLMs is strongly preferred

🎯 Experience with prompting, RAG, embeddings, vector stores or fine-tuning is beneficial

🎯 Experience using AI-assisted development tools such as GitHub Copilot or Claude Code

🎯 Strong software engineering and problem-solving skills

🌟Preferred Skills:
✅ Machine Learning 🤖

✅ MLOps

✅ Apache Spark

✅ PyTorch / TensorFlow

✅ Python

✅ Big Data Engineering

✅ Distributed Systems

✅ Cloud Computing ☁️

✅ ML Model Monitoring

✅ CI/CD

✅ Model Deployment

✅ Generative AI

✅ Large Language Models

✅ RAG & Vector Databases

✅ AI-Assisted Software Engineering

🌟Why Consider Expedia Group?
✅ Work on ML systems operating at global scale 🌎

✅ Build technology used by millions of travelers

✅ Work at the intersection of AI, big data and software engineering

✅ Gain exposure to production-grade MLOps

✅ Work with modern ML and GenAI technologies

✅ Collaborate with global engineering teams

✅ Opportunity to mentor and influence engineering practices

✅ Build systems where reliability and scale actually matter

Expedia Group’s careers site also highlights Bengaluru as one of its featured global locations and promotes technology opportunities across its organization.

🔥Career Insight:
The ML industry is moving beyond:

“Can you build a model?”

The better question is:

“Can you make that model work reliably at scale?”

That’s where MLOps becomes valuable.

Training is only one part of the journey.

Production introduces:

Data drift.
Latency.
Infrastructure costs.
Model failures.
Monitoring.
Security.
Scalability.

Engineers who can solve those problems aren’t just building models.

They’re building systems.

And that’s increasingly where the biggest opportunities in AI engineering are moving.