Job Description
We are seeking a visionary AI Architect to spearhead our initiatives for the 2026 roadmap. In this pivotal role, you will design and implement next-generation Generative AI systems that will define the future of human-computer interaction. You will work at the intersection of research and production, leveraging cutting-edge Large Language Models (LLMs) to build scalable, safe, and impactful solutions for enterprise clients.
Why Join Us?
At FutureScale Solutions, we are not just building tools for today; we are architecting the intelligence layer for tomorrow. You will have the autonomy to experiment, the resources to innovate, and the opportunity to lead a world-class team in a dynamic, fast-paced environment.
Responsibilities
- Design and architect end-to-end Generative AI pipelines, including data ingestion, model training, fine-tuning, and deployment.
- Lead research and development efforts focused on enhancing model accuracy, reducing hallucinations, and improving inference latency.
- Collaborate with product managers and engineers to translate complex business requirements into technical AI solutions.
- Implement robust guardrails and safety protocols to ensure responsible AI deployment.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Stay ahead of the curve on the latest advancements in Natural Language Processing (NLP) and Multimodal AI.
Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, or a related technical field (or equivalent practical experience).
- Minimum of 5 years of experience in software engineering, with at least 3 years specializing in Deep Learning and Machine Learning.
- Deep proficiency in Python and experience with frameworks such as PyTorch, TensorFlow, or JAX.
- Proven track record of working with Large Language Models (GPT, Llama, etc.) and RAG (Retrieval-Augmented Generation) architectures.
- Strong understanding of distributed systems, cloud infrastructure (AWS/Azure/GCP), and MLOps practices.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.