If you’re aiming to work on cutting-edge AI systems, the Machine Learning Engineer role at Sarvam in Bangalore is one of the most exciting opportunities right now.
This role focuses on vision-language models (VLMs), multimodal AI, and large-scale deep learning systems, making it ideal for professionals who want to work on impactful, real-world AI problems.
Apply NowAbout Sarvam and the Role
Sarvam is an emerging AI company focused on building India’s sovereign AI ecosystem, working across research, infrastructure, and AI-powered applications.
As a Machine Learning Engineer (Vision), you’ll be part of a team developing systems that can understand both images and text simultaneously—a key area in modern AI.
This role is not just about experimentation—it involves building production-ready AI systems that can scale and solve real business and societal problems.
What Does a Machine Learning Engineer at Sarvam Do?
In simple terms, you will handle the complete lifecycle of machine learning models, from raw data to deployment.
Key Responsibilities
- Design and build training pipelines for large-scale vision-language models
- Work with GPU clusters and distributed systems for model training
- Develop multimodal data pipelines for:
- Data ingestion
- Cleaning and filtering
- Deduplication
Model Development & Optimization
- Implement advanced transformer-based architectures
- Experiment with new techniques from AI research
- Fine-tune large models for better performance
Evaluation & Performance
- Build evaluation frameworks and benchmarks
- Track performance using automated systems
- Improve model accuracy, latency, and scalability
Production & Deployment
- Optimize models using:
- Quantization
- Batching
- Efficient inference techniques
- Build production-grade AI systems and pipelines
- Work on retrieval-augmented generation (RAG) workflows
Collaboration & Problem Solving
- Translate real-world problems into machine learning solutions
- Work with clients on use cases like:
- Document processing
- Visual search
- Data extraction
- Debug and improve deployed models
Skills Required for Machine Learning Engineer Role
To succeed in this role, you need strong fundamentals in AI, programming, and system design.
Educational Qualification
- Bachelor’s degree in:
- Computer Science
- Statistics
- Physics
- Or related technical fields
Technical Skills
- Strong programming skills in Python
- Hands-on experience with PyTorch
- Deep understanding of:
- Transformer architectures
- Deep learning techniques
Advanced Knowledge (Preferred)
- Experience with:
- Large-scale model training
- Distributed systems
- Familiarity with frameworks like:
- FSDP
- DeepSpeed
- Megatron-LM
- Understanding of:
- Multimodal AI systems
- Retrieval-Augmented Generation (RAG)
Optimization & Systems Skills
- Knowledge of:
- Quantization
- Model distillation
- Efficient inference
- Experience building data pipelines for ML workflows
Additional Qualities
- Strong problem-solving mindset
- Ability to work in fast-paced and ambiguous environments
- Open-source contributions or a strong GitHub profile (highly valuable)
Salary for Machine Learning Engineer at Sarvam
The expected salary range for this role is:
👉 ₹20 LPA to ₹45 LPA
Salary depends on:
- Experience (2–5 years)
- Depth in AI/ML and deep learning
- Hands-on project or research experience
Additional benefits may include:
- Performance bonuses
- Stock options
- Opportunity to work on cutting-edge AI innovations
Why This Role is High-Value in 2026
This is not a typical ML job. Here’s why it stands out:
- Work on next-gen AI (Vision + Language models)
- Build systems at national scale impact
- Exposure to real production AI systems, not just theory
- Strong demand for multimodal AI engineers globally
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FAQs – Machine Learning Engineer at Sarvam
1. What does a Machine Learning Engineer (Vision) do?
They build AI systems that can understand both images and text, working on models like vision-language systems and multimodal AI pipelines.
2. Is this role suitable for beginners?
No, this role typically requires 2–5 years of experience in machine learning, deep learning, or related fields.
3. Which programming language is most important?
Python is essential, especially with frameworks like PyTorch.
4. What are vision-language models (VLMs)?
VLMs are AI models that can process and understand both visual data (images) and text, enabling applications like image captioning and visual search.
Apply Now