Job Description
We are building the intelligent infrastructure for the year 2026. NeuralCore Systems is seeking a visionary Senior AI Architect to lead the development of next-generation generative models and autonomous systems. In this role, you will bridge the gap between cutting-edge research and scalable production deployment, defining the roadmap for our AI products for the next decade.
You will work in a collaborative, high-performance environment where innovation is not just encouraged but required. If you are passionate about solving complex problems at the intersection of machine learning, distributed systems, and ethical AI, we want to hear from you.
Why Join Us?
- Work on projects that define the future of AI.
- Competitive compensation and equity package.
- Top-tier benefits and flexible work arrangements.
- Access to state-of-the-art compute infrastructure.
Responsibilities
- Architect and implement scalable LLM (Large Language Model) pipelines optimized for the 2026 deployment horizon.
- Lead research initiatives into emerging AI paradigms, including multimodal learning and reinforcement learning agents.
- Optimize model inference latency and throughput to support real-time applications.
- Establish best practices for MLOps, including model versioning, A/B testing, and automated retraining pipelines.
- Collaborate with product teams to translate complex technical requirements into robust AI solutions.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- 7+ years of professional experience in software engineering, with at least 4 years focused on Machine Learning/AI.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Strong background in Natural Language Processing (NLP) and Generative AI architectures.
- Experience with distributed systems and cloud platforms (AWS, GCP, or Azure).
- Proven track record of deploying large-scale machine learning models into production environments.