Siemens Energy is hiring for the AI/Machine Learning Engineer role in Gurgaon, Haryana. This is a full-time entry-level opportunity for fresh graduates and early-career candidates interested in Artificial Intelligence, Machine Learning, NLP, Generative AI, and backend AI systems.
This opportunity is especially valuable for candidates wanting hands-on exposure to:
- Machine Learning Pipelines
- Generative AI
- RAG Applications
- NLP Workflows
- AI Product Deployment
If you want to work on AI solutions in the energy sector and contribute to large-scale industrial transformation, this role is worth considering.
About the Company
Siemens Energy is one of the world’s leading energy technology companies, operating in more than 90 countries with around 100,000 employees worldwide.
The company focuses on:
- Energy generation
- Power transmission
- Decarbonization
- Grid modernization
- Renewable energy solutions
Siemens Energy contributes to approximately one-sixth of global electricity generation, making it a major player in the energy industry.
Its mission is to make energy:
- Sustainable
- Reliable
- Affordable
Key Responsibilities
ML Pipeline Development
You will assist in building ML pipelines covering:
- Data preprocessing
- Model training
- Evaluation
- Inference
This includes preparing data and ensuring models perform reliably in production.
Generative AI & RAG Workflows
One of the most exciting parts of this role is working with Generative AI.
You may support:
- LLM-based workflows
- Prompt engineering
- RAG systems
- AI assistants
RAG (Retrieval-Augmented Generation) helps AI systems retrieve relevant context before generating responses.
This is highly relevant for enterprise AI applications.
NLP Engineering
You will work on text-related AI tasks such as:
- Data cleaning
- Parsing
- Chunking
- Embeddings
- Semantic search
This helps build intelligent systems for processing documents and business knowledge.
Backend API Development
You will help expose AI functionality via APIs using frameworks like:
- FastAPI
These APIs allow applications to interact with ML models.
Typical use cases:
- Prediction APIs
- Chat assistants
- Search systems
- AI automation tools
Model Optimization
You will help improve:
- Accuracy
- Latency
- Scalability
- Reliability
Optimization ensures AI systems remain efficient in production.
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Required Technical Skills
Python Programming
Strong Python knowledge is essential.
Python is widely used for:
- ML development
- Data analysis
- Backend APIs
- AI workflows
You should know:
- Functions
- OOP
- Data structures
- Debugging
Machine Learning Fundamentals
You need a solid understanding of:
- Supervised learning
- Unsupervised learning
- Overfitting
- Evaluation metrics
Common algorithms include:
- Regression
- Classification
- Clustering
AI/ML Libraries
Expected exposure to:
- NumPy
- Pandas
- scikit-learn
Preferred deep learning exposure:
- PyTorch
- TensorFlow
These libraries are used for training and evaluating models.
Generative AI Knowledge
Bonus if you understand:
- Large Language Models (LLMs)
- Prompt engineering
- Vector embeddings
- Retrieval systems
Knowledge of GenAI makes you highly competitive.
Backend & APIs
Basic backend knowledge is important.
You should understand:
- REST APIs
- Request-response lifecycle
- Authentication basics
API integration is critical in AI production systems.
Cloud Knowledge
Bonus if you have exposure to:
- Amazon Web Services
- Microsoft Azure
Cloud knowledge helps with:
- Deployment
- Scaling
- Storage
- Model serving
Version Control
Knowledge of:
- Git
Useful for:
- Collaboration
- Code management
- Reviews
Educational Qualification
Eligible candidates typically have degrees in:
- Computer Science
- Information Technology
- AI / ML
- Data Science
- Related engineering fields
Fresh graduates with strong projects can apply.
Company Rating & Reviews
Overall Rating: ⭐⭐⭐⭐☆ (4.4/5)
What Employees Like
- Strong global brand value
- Excellent learning opportunities
- Good work-life balance
- Exposure to industrial-scale technology
- Stable career growth
Things to Consider
- Enterprise workflows can be process-heavy
- Some teams move slower than startups
- Cross-team collaboration can be complex
Best for: Candidates looking for long-term growth in AI + enterprise technology.
Salary
Siemens Energy has not officially disclosed salary for this role.
Estimated Salary (Based on similar entry-level AI/ML roles)
| Salary Component | Estimated Range |
|---|---|
| Annual CTC | ₹8 – ₹18 LPA |
| Monthly Equivalent | ₹66,000 – ₹1.5L/month |
Salary may vary based on:
- Education
- AI/ML projects
- Python expertise
- NLP knowledge
- Interview performance
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Soft Skills Required
Siemens Energy values candidates who can:
Learn Quickly
AI evolves rapidly, so adaptability matters.
Solve Problems
You should break complex problems into manageable parts.
Collaborate
AI development requires teamwork across technical and business teams.
Communicate Clearly
Explaining AI systems simply is an important skill.
How to Apply
Before applying:
- Update resume
- Highlight AI/ML projects
- Add GitHub links
- Mention GenAI experiments
- Showcase cloud/API exposure
Candidates with practical projects usually stand out.
Disclaimer:
This information is collected from official/public sources for informational purposes only. Salary estimates are based on market research and may vary. We do not charge any fee for job updates and do not guarantee selection or recruitment. Candidates should verify details from the official source before applying.
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