Job Description
We are at the forefront of the AI revolution, building the intelligent systems that will define the next decade of human interaction. As a Senior Generative AI Engineer, you will not just use existing models; you will architect, train, and deploy next-generation Large Language Models (LLMs) and multimodal agents. Join a team of world-class researchers and engineers dedicated to pushing the boundaries of artificial general intelligence.
In this pivotal role, you will be responsible for the full lifecycle of AI model development, from foundational architecture design to production-grade deployment. You will collaborate with product leaders to solve complex, high-impact problems and ensure our AI solutions are scalable, efficient, and aligned with ethical standards.
Why Join Us?
- Work on cutting-edge technology that impacts millions of users.
- Competitive compensation package including equity and performance bonuses.
- Flexible work environment and top-tier benefits.
Responsibilities
- Model Architecture: Design and implement novel architectures for Large Language Models (LLMs) and multimodal systems to enhance performance and reduce inference costs.
- Fine-tuning & Optimization: Perform advanced fine-tuning techniques (LoRA, QLoRA, P-Tuning) on proprietary and open-source foundation models to adapt them for specific enterprise use cases.
- RAG Pipelines: Build robust Retrieval-Augmented Generation (RAG) systems and vector databases to ensure model accuracy and up-to-date knowledge retrieval.
- Agent Development: Develop autonomous AI agents capable of complex reasoning, tool use, and multi-step planning in dynamic environments.
- Production Deployment: Deploy models using MLOps best practices, ensuring high availability, low latency, and seamless integration into existing software ecosystems.
- Ethical AI: Implement safety guardrails and alignment techniques to mitigate biases and ensure responsible AI deployment.
- Research: Stay ahead of the curve by exploring emerging research papers and integrating new methodologies into our production stack.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Machine Learning, or a related field (or equivalent professional experience).
- Technical Mastery: Deep understanding of Deep Learning, Natural Language Processing (NLP), and Transformer architectures.
- Programming: Proficiency in Python, PyTorch, and TensorFlow. Experience with C++ for high-performance computing is a plus.
- Frameworks: Extensive experience with Hugging Face Transformers, LangChain, LlamaIndex, and model serving frameworks (vLLM, TGI, Ray).
- Data Engineering: Strong skills in data preprocessing, cleaning, and managing large-scale training datasets.
- Soft Skills: Excellent problem-solving abilities and the capacity to communicate complex technical concepts to non-technical stakeholders.
- Experience: 5+ years of experience in software engineering or data science, with at least 2 years focused on Generative AI or LLM development.