Generative AI Systems Engineer – Vision-Language Models

Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

Role Summary

We are seeking aGenerative AI Systems Engineer to design, evaluate, and optimizeVision-Language Model (VLM) systems for real-world applications.

This role requires a combination of:

• Model understanding
• Experimental rigor
• Systems and production thinking

You will work onbenchmarking, fine-tuning, and deploying multimodal models, with a strong emphasis ontradeoff analysis across accuracy, latency, and cost.

Key Responsibilities

Model Evaluation & Benchmarking

• Evaluate pretrained VLMs on domain-specific datasets
• Define and justify appropriateevaluation metrics
• Analyze model behavior, includingsystematic failure modes

Model Adaptation & Fine-Tuning

• Implement parameter-efficient fine-tuning techniques (e.g.,LoRA, QLoRA)
• Optimize training underlimited data and compute constraints
• Makedata-centric and model-centric improvements with clear justification

Experimental Rigor

• Design controlled experiments to compare baseline vs improved models
• Quantify improvements across:
  • accuracy
  • latency
  • cost
• Provide clear, defensible explanations for observed outcomes

System Design & Deployment

• Architect scalable inference pipelines for multimodal models
• Optimize for:
  • low latency
  • high throughput
  • cost efficiency
• Implement serving layers (API/service) with reproducible environments

Data Engineering

• Build pipelines to process and align:
  • images
  • textual queries
  • structured metadata
• Analyze dataset characteristics, includingbiases and distribution gaps

B.E/B. Tech

• 5–7 years of industry experience in ML/AI systems
• Strong proficiency inPython and ML frameworks (e.g., PyTorch)
• Experience withVLMs,LLMs or any other multimodal models
• Understanding ofmodel evaluation and experimentation practices
• Familiarity withML system design (inference, scaling, optimization)

Preferred Qualifications

• Experience withVision-Language Models (e.g., LLaVA, BLIP, Flamingo-style architectures)
• Hands-on experience withparameter-efficient fine-tuning methods
• Knowledge ofmodel optimization techniques:
  • quantization
  • batching
  • caching (e.g., embedding reuse)
• Experience withDocker / containerized deployments
• Exposure tolarge-scale or real-world datasets