Job Description
We are on a mission to engineer the intelligence of tomorrow. Nebula AI Solutions is seeking a visionary Senior AI/ML Architect to define the roadmap for our next-generation Large Language Models (LLMs) and autonomous agents. This role is pivotal in shaping the technological trajectory that will define the industry landscape in 2026 and beyond.
If you are passionate about pushing the boundaries of Generative AI, responsible machine learning, and scalable infrastructure, we want to meet you. You will work alongside world-class researchers and engineers to build systems that are not just smart today, but future-proof for the decade ahead.
Why Join Us?
- Future-Ready Tech Stack: Work with the latest in PyTorch, TensorFlow, and cutting-edge MLOps tools.
- Premier Location: Collaborate from our state-of-the-art HQ in the heart of San Francisco.
- Impact: Your work will directly influence how billions of users interact with AI in the coming years.
Responsibilities
- Design and architect scalable Deep Learning and Generative AI infrastructure capable of handling enterprise-grade workloads.
- Lead the research and implementation of fine-tuning strategies for Large Language Models (LLMs) to enhance domain-specific performance.
- Optimize model inference pipelines to ensure low-latency, high-throughput responses for real-time applications.
- Establish best practices for Responsible AI, including bias mitigation, transparency, and ethical guidelines.
- Collaborate cross-functionally with Product Managers and Data Scientists to translate business requirements into technical solutions.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in machine learning engineering, deep learning, or NLP.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; experience with Hugging Face Transformers; familiarity with cloud platforms (AWS/GCP/Azure).
- Architecture: Strong understanding of distributed systems, containerization (Docker/Kubernetes), and MLOps practices.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems in ambiguous environments.
- Communication: Exceptional written and verbal communication skills with the ability to explain technical concepts to non-technical stakeholders.