Eucloid - Lead Data Scientist - Vision & Multimodal AI
Posted on: 03/03/2026
Job Description
Description :
We are looking for a Lead Data Scientist Vision & Multimodal AI to architect and build next-generation Vision-Language Model (VLM) systems at scale.
This role requires deep expertise in :
- Architecting and implementing RLHF (Reinforcement Learning from Human Feedback) Frameworks.
- Training and fine-tuning Open-Source Vision-Language Models (VLMs).
- Deploying and scaling multimodal models to production serving millions of requests.
Key Responsibilities :
Architect & Build RLHF Frameworks :
- Design end-to-end RLHF pipelines (SFT - Reward Modeling - PPO/DPO)
- Develop scalable human feedback collection systems
- Implement preference modeling and ranking pipelines
- Optimize reward models for multimodal outputs (image + text)
- Build automated evaluation frameworks
Train & Fine-Tune OSS Vision-Language Models :
- Experience working with Qwen-VL, Llama, GPT OSS
- Pretraining / instruction tuning multimodal models
- Parameter-efficient fine-tuning (LoRA, QLoRA)
- Dataset curation & synthetic data generation
- Scaling training on multi-GPU / multi-node clusters
- Optimizing for alignment, hallucination reduction, and safety
Highly Scalable Deployment of VLM Systems :
- Design distributed inference pipelines (GPU-optimized)
- Model serving using vLLM and Triton Inference Server
- Optimize latency, throughput, and cost
- Implement batching, KV caching, quantization, tensor parallelism
- Deploy on Kubernetes-based infrastructure
- Build monitoring for drift, performance, and hallucinations
Multimodal AI System Design :
- Architect systems combining OCR, vision encoders, LLMs, retrieval
- Implement retrieval-augmented multimodal pipelines
- Design evaluation benchmarks for VQA, grounding, and reasoning
- Ensure model safety and guardrails
Technical Leadership :
- Lead a team of ML engineers & research scientists
- Define technical roadmap for multimodal AI
- Review model architectures & code quality
- Collaborate with product and infrastructure teams.
Qualifications :
- 6+ years in ML / AI
- 2+ years working with large-scale LLM or VLM systems
- Strong hands-on experience building RLHF pipelines (not just using libraries)
- Deep PyTorch expertise
- Experience training models >7B parameters
- Experience with distributed training (Deep Speed, FSDP)
- Production-grade deployment experience handling 10k+ QPS workloads
- Strong understanding of transformer architectures.
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Posted by
43
Posted in
AI/ML
Functional Area
Data Science
Job Code
1617611
