Gen AI Engineer II

Company Description

Eros Innovation is a global technology company operating at the intersection of Artificial Intelligence, media, and next-generation digital platforms. We focus on building advanced Generative AI solutions, multimodal systems, and scalable AI infrastructure that power real-world enterprise applications.

At the core of our ecosystem is Eros Gen AI our proprietary Generative AI platform designed to deliver cutting-edge capabilities across large language models (LLMs), vision-language systems, speech AI, and retrieval-augmented intelligence. Eros Gen AI drives both research innovation and production-grade deployments, enabling intelligent automation and AI-driven transformation at scale.

If youre passionate about building impactful AI systems and working on frontier technologies, Eros Innovation is where innovation meets execution.

Role Description

We are seeking a highly skilled Gen AI Engineer who can drive the development, optimization, and deployment of advanced LLMs, VLMs, and multimodal AI systems. You will lead the GenAI team, translate business requirements into technical solutions, fine-tune foundation models, design retrieval architectures, and ensure all models are production-ready with optimized inference pipelines.

Lead the design, development, and enhancement of LLMs, VLMs, RAG systems, and multimodal generation pipelines for production use cases.

Understand business requirements and convert them into scalable, high-performance AI model architectures and workflows.

Fine-tune and customize Transformer-based models using proprietary datasets, advanced training strategies, and evaluation frameworks.

Optimize tokenization, embedding generation, vector search, and retrieval flows for high-throughput applications.

Develop high-performance inference pipelines using ONNX, TensorRT, quantization, batching, streaming, and GPU/accelerator optimizations.

Ensure all models are production-graderobust, scalable, monitored, and integrated into backend systems.

Lead and mentor the Gen AI engineering team, conduct code/model reviews, and drive overall technical direction.

Research and evaluate cutting-edge architectures in multimodal models, generative AI, and retrieval-augmented techniques.

Architect end-to-end Gen AI systems including training, fine-tuning, inference Serving, and continuous model improvements.

Work with backend teams to integrate models into scalable APIs using Triton, TensorRT, ONNX Runtime, vLLM, or custom inference engines.

Build model evaluation pipelines BLEU, ROUGE, alignment tests, hallucination checks, safety filters, and latency/throughput benchmarks.

Own the roadmap for LLM/VLM improvements and drive experimentation with new architectures (Mixture-of-Experts, diffusion-based multimodal, etc.).

Collaborate cross-functionally with product, backend, ML, and DevOps teams to deliver end-to-end Gen AI features.

Maintain documentation, ensure reproducibility, and follow best practices in model governance, versioning, and monitoring.

Mentor the team in training deep learning models, optimizing memory/GPU usage, and deploying large-scale inference systems.

Qualifications

46 years of experience in applied machine learning, deep learning, GenAI, or multimodal systems.

Proven expertise with Transformers, LLMs, VLMs, diffusion models, and retrieval-augmented systems.

Hands-on experience with Python, PyTorch, TensorFlow, Hugging Face, LangChain, and modern training pipelines.

Strong knowledge of vector databases (FAISS, Pinecone, Milvus, Chroma).

Expert-level experience with ONNX, TensorRT, quantization, model optimization, and inference engines (vLLM, FasterTransformer, Triton).

Solid understanding of distributed training, GPU utilization, mixed precision, and large-scale model serving.

Ability to lead teams, plan AI architecture, review work, and deliver production-quality AI