Job Description
Are you ready to architect the future of AI? Nexus Future Systems is looking for a visionary AI & Machine Learning Architect to lead our 2026 roadmap. If you thrive at the intersection of cutting-edge technology and strategic growth, this is your opportunity to shape the digital landscape of tomorrow.
We are not just building software; we are building the intelligent systems that will define the next decade. You will work with a world-class team to design, deploy, and scale robust machine learning solutions that solve complex, real-world problems.
Why Join Us?
- Work on next-generation AI technologies with direct impact on global markets.
- Competitive compensation and equity package.
- Flexible remote-first culture with hubs in San Francisco and New York.
Responsibilities
- Lead Strategic Roadmap: Define and execute the technical vision for AI capabilities leading up to and beyond 2026, ensuring alignment with business goals.
- Model Architecture: Design and implement scalable machine learning architectures for NLP, Computer Vision, and predictive analytics.
- Technical Mentorship: Mentor a team of data scientists and engineers, fostering a culture of innovation and continuous learning.
- Performance Optimization: Oversee the optimization of model performance, reducing latency and improving inference speed in production environments.
- Collaboration: Partner with cross-functional teams (Product, Engineering, Data) to integrate AI solutions seamlessly into existing workflows.
- R&D: Stay ahead of industry trends and research emerging technologies (e.g., LLMs, Federated Learning) to apply them to our product suite.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field. PhD preferred.
- Experience: 5+ years of experience in Machine Learning, with at least 2 years in a senior architectural or lead role.
- Technical Stack: Proficiency in Python, TensorFlow, PyTorch, and experience with cloud platforms like AWS or GCP.
- Skills: Strong understanding of distributed systems, MLOps, and data pipelines.
- Communication: Exceptional ability to translate complex technical concepts into actionable insights for non-technical stakeholders.
- Problem Solving: Demonstrated track record of solving high-impact technical challenges in production environments.