Job Description
Shape the Future of Intelligence. FutureScale Inc. is a premier technology firm pioneering the next generation of Generative AI solutions. We are looking for a visionary Senior GenAI Engineer to lead our research and development division, focusing on Large Language Models (LLMs) and autonomous agents.
In this high-impact role, you will be at the forefront of the 2025/2026 technology landscape, architecting scalable AI systems that drive enterprise innovation. You will collaborate with world-class researchers and product engineers to deliver solutions that are not only technically superior but also ethically sound.
What You'll Do:
- Architect and deploy state-of-the-art Generative AI models and LLMs.
- Design Retrieval-Augmented Generation (RAG) pipelines to enhance model accuracy and context.
- Optimize model inference for latency and cost-efficiency in production environments.
- Implement rigorous testing and evaluation frameworks for AI safety and reliability.
- Mentor junior engineers and foster a culture of continuous learning in AI research.
Who You Are:
- A deep technical expert with a Master’s or PhD in Computer Science, AI, or a related field.
- 5+ years of hands-on experience with Python, PyTorch, or TensorFlow.
- Proven track record of deploying NLP models at scale in cloud environments.
- Strong knowledge of MLOps, data governance, and ethical AI principles.
- A passion for the evolving landscape of AI and its potential to transform industries.
Responsibilities
- Develop and fine-tune foundation models using modern deep learning frameworks.
- Build and maintain robust RAG architectures to improve factual accuracy.
- Collaborate with cross-functional teams to integrate AI features into consumer products.
- Monitor model performance and implement A/B testing strategies.
- Contribute to the open-source community and stay ahead of AI trends.
Qualifications
- PhD or Master’s in Computer Science, Mathematics, or a related technical field.
- 5+ years of experience in Machine Learning, Deep Learning, or NLP.
- Expert proficiency in Python, PyTorch, and Hugging Face Transformers.
- Experience with vector databases (Pinecone, Milvus) and vector embeddings.
- Familiarity with cloud platforms (AWS/GCP) and containerization (Docker/Kubernetes).