If you are looking for a high-impact Machine Learning Engineer role in Bengaluru, this opportunity at eBay can be a strong career move. The company is building advanced recommendation systems powered by AI, deep learning, NLP, LLMs, and large-scale data pipelines.
This article provides a complete overview of the Machine Learning Engineer role, required skills, responsibilities, eligibility, and career growth opportunities.
- 1 About eBay – Reinventing Global Commerce
- 2 📌 Machine Learning Engineer – Job Overview
- 3 🚀 Key Responsibilities of a Machine Learning Engineer
- 4 🧠 Technical Skills Required
- 5 🔬 Technologies Used by the Team
- 6 🎓 Educational Qualification
- 7 💡 Why This Machine Learning Engineer Role is High Impact
- 8 🌍 Career Growth for a Machine Learning Engineer
- 9 🏆 What Makes This Role Special?
- 10 📈 Who Should Apply?
- 11 🔎 Final Thoughts on the Machine Learning Engineer Role
About eBay – Reinventing Global Commerce
eBay is a global ecommerce leader operating in more than 190 markets. Millions of buyers and sellers use the platform every day. Behind the scenes, intelligent recommendation systems powered by AI help users discover products quickly and efficiently.
The Machine Learning Engineer role is part of the Recommendations (Recs) team, which builds real-time recommendation systems for web and mobile platforms.
📌 Machine Learning Engineer – Job Overview
| Job Detail | Information |
|---|---|
| Role | Machine Learning Engineer |
| Location | Bengaluru, India |
| Department | Engineering |
| Work Mode | Onsite |
| Level | T24 |
| Experience | 1+ Years (MS) or 3+ Years (BS) |
| Focus Area | Recommendation Systems, AI, GenAI, LLM |
This Machine Learning Engineer position focuses on building scalable AI-driven recommendation engines that impact millions of users globally.
🚀 Key Responsibilities of a Machine Learning Engineer
A Machine Learning Engineer in this team will:
- Build and deploy deep learning-based recommendation systems.
- Develop machine-learned ranking models.
- Work on GenAI/LLM-powered recommendation engines.
- Build large-scale distributed systems.
- Create real-time data pipelines using big data technologies.
- Deploy models into production environments.
- Integrate AI solutions with Google Cloud platforms (GCP Vertex AI).
This role directly influences how users interact with eBay’s product discovery experience.
🧠 Technical Skills Required
To become a successful Machine Learning Engineer, candidates should have:
Programming & Engineering Skills
- Strong expertise in Scala, Java, or similar OO/functional languages.
- Experience building distributed applications.
- Experience with NoSQL databases (MongoDB, Redis).
- Understanding of scalable system architecture.
AI & Machine Learning Skills
- Deep learning for recommendation systems.
- NLP and LLM experience.
- Prompt engineering knowledge.
- RAG (Retrieval-Augmented Generation) exposure.
- AI model deployment experience.
Big Data & Cloud Skills
- Hadoop, Spark, Flink pipelines.
- Google Cloud Platform (GCP preferred).
- Experience with production-grade MLOps.
🔬 Technologies Used by the Team
The Machine Learning Engineer team works with:
- Google Cloud Vertex AI
- Hadoop & Spark
- Large Language Models (LLMs)
- GenAI-based systems
- Big data distributed pipelines
- Real-time recommendation architecture
This is a production-scale industrial AI environment.
🎓 Educational Qualification
| Qualification | Requirement |
|---|---|
| Master’s Degree | MS in Computer Science or related field + 1 year experience |
| Bachelor’s Degree | BS/BA in CS or related + 3 years experience |
| Preferred | AI/ML applied research exposure |
Candidates with strong applied AI experience are highly preferred.
💡 Why This Machine Learning Engineer Role is High Impact
This is not a research-only role. It is a production-facing engineering position where:
- AI models directly impact user experience.
- Recommendation algorithms drive revenue growth.
- Models operate on billions of data points.
- Systems serve millions of users in near real-time.
If you want measurable business impact as a Machine Learning Engineer, this opportunity stands out.
🌍 Career Growth for a Machine Learning Engineer
Working in a high-scale ecommerce ecosystem helps you:
- Gain exposure to industrial-scale AI.
- Work with multimodal datasets.
- Deploy GenAI solutions in production.
- Collaborate with applied research engineers.
- Build expertise in recommendation systems.
Long-term career paths include:
- Senior Machine Learning Engineer
- Applied AI Scientist
- MLOps Architect
- AI Platform Engineer
🏆 What Makes This Role Special?
- Work with multimodal unstructured data.
- Production-level LLM deployment.
- Integration with cloud AI platforms.
- Real-time personalization systems.
- Exposure to advanced AI research and innovation.
This Machine Learning Engineer position combines applied research with production engineering — a powerful combination for long-term career growth.
📈 Who Should Apply?
This opportunity is ideal for:
- Engineers with distributed systems experience.
- Developers passionate about AI at scale.
- Professionals experienced in recommendation systems.
- Candidates comfortable working with large datasets.
- ML engineers who want to work with GenAI and LLMs in production.
🔎 Final Thoughts on the Machine Learning Engineer Role
The Machine Learning Engineer position in Bengaluru offers exposure to:
- Large-scale AI infrastructure
- Industrial recommendation engines
- Big data engineering
- Cloud AI platforms
- GenAI-based personalization systems
If you are looking to advance your career in AI, recommender systems, deep learning, and large-scale data engineering, this Machine Learning Engineer role can provide strong technical growth and global exposure.
✨ Stay consistent, keep upgrading your skills in AI and distributed systems, and continue applying for relevant roles. The right opportunity can shape your future in technology.
