Job Description
Are you ready to engineer the breakthroughs that will define the decade? OmniStream Technologies is seeking a visionary Senior AI Architect to lead our research into next-generation autonomous systems and generative AI models.
In this pivotal role, you won't just be maintaining systems; you will be architecting the intelligent infrastructure that powers the technological landscape of 2026 and beyond. We are looking for a technical leader who thrives at the intersection of deep learning, scalable cloud architecture, and ethical AI implementation.
Join us in shaping the future of intelligent computing. If you are passionate about pushing the boundaries of what is possible with Artificial Intelligence, we want to hear from you.
Responsibilities
- Architect End-to-End AI Pipelines: Design, build, and deploy scalable machine learning and deep learning models that integrate seamlessly into our production environment.
- Lead Research & Innovation: Spearhead research into Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and autonomous agent frameworks to stay ahead of industry trends.
- Optimize Performance: Drive the optimization of model inference latency and resource efficiency to ensure real-time, high-performance applications.
- Ensure Ethical AI: Implement rigorous testing and bias mitigation strategies to ensure our AI systems are fair, transparent, and safe for enterprise deployment.
- Mentorship & Culture: Guide a team of junior engineers and data scientists, conducting code reviews and fostering a culture of continuous learning and technical excellence.
- Collaborative Strategy: Partner with product and engineering teams to define technical roadmaps and translate business requirements into robust AI solutions.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: 7+ years of professional experience in AI/ML engineering, with at least 3 years in a senior leadership or architectural role.
- Technical Proficiency: Expert-level knowledge of Python, PyTorch, TensorFlow, or JAX. Deep experience with deep learning architectures (CNNs, RNNs, Transformers).
- Cloud & Infrastructure: Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- MLOps: Proven track record in implementing MLOps pipelines, CI/CD, and model versioning strategies.
- Problem Solving: Exceptional ability to solve complex, unstructured problems and translate them into scalable technical solutions.