Job Description
Are you ready to architect the next generation of artificial intelligence?
Nexus Future Systems is on a mission to define the technological landscape of 2026 and beyond. We are seeking a visionary Senior AI & Machine Learning Engineer to lead our Advanced Intelligence division. In this pivotal role, you will be responsible for designing scalable, robust, and ethical AI systems that power our next-generation products. You will work at the intersection of deep learning, generative AI, and strategic product engineering.
Why Join Us?
- Shape the Future: Work on projects directly influencing our 2026 product roadmap.
- Elite Team: Collaborate with world-class researchers and engineers.
- Impact: Deploy models that serve millions of users globally.
We offer a competitive salary, equity package, and the flexibility to work from our state-of-the-art office in the heart of San Francisco.
Responsibilities
- Architect and Deploy: Design, build, and deploy high-performance machine learning models and generative AI pipelines using Python, PyTorch, and TensorFlow.
- Model Optimization: Optimize existing models for speed, accuracy, and cost-efficiency in production environments.
- Strategic Roadmap: Contribute to the technical strategy for the 2026 release cycle, identifying emerging AI trends and integrating them into our stack.
- Collaboration: Partner with data scientists, product managers, and engineers to translate complex business requirements into technical solutions.
- MLOps Implementation: Establish and maintain CI/CD pipelines for machine learning, ensuring reproducibility and automated testing.
- Code Review & Mentorship: Lead code reviews and mentor junior engineers, fostering a culture of technical excellence and innovation.
Qualifications
- Experience: 5+ years of professional experience in software engineering or machine learning.
- Core Skills: Proficiency in Python, SQL, and experience with deep learning frameworks (PyTorch or TensorFlow).
- Generative AI: Strong understanding of Large Language Models (LLMs), transformers, and prompt engineering.
- Infrastructure: Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver scalable solutions.
- Communication: Excellent verbal and written communication skills; ability to explain technical concepts to non-technical stakeholders.