Job Description
We are Nexus 2026, a pioneering technology firm dedicated to architecting the future of intelligent systems. We are seeking a visionary Senior AI & Machine Learning Architect to lead our research and engineering division. If you are passionate about pushing the boundaries of what is possible in 2026 and beyond, we want to meet you.
In this role, you will define the architectural vision for our next-generation AI platforms, ensuring scalability, efficiency, and ethical AI integration. You will work at the intersection of deep learning, distributed systems, and cloud infrastructure to solve complex, real-world problems.
Why Join Us?
- Work on cutting-edge AI projects that shape the industry.
- Competitive compensation and equity package.
- Flexible remote and hybrid work options.
- Opportunity to mentor the next generation of AI engineers.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable machine learning pipelines and distributed AI systems that can handle petabyte-scale data.
- Model Development: Lead the research and development of state-of-the-art deep learning models, including NLP, Computer Vision, and Reinforcement Learning.
- Technical Strategy: Translate business requirements into robust technical roadmaps, evaluating new technologies and frameworks to drive innovation.
- Team Mentorship: Provide technical guidance and mentorship to senior engineers and data scientists, fostering a culture of continuous learning and best practices.
- Performance Optimization: Rigorously optimize model latency and throughput, ensuring our AI solutions provide real-time responses.
- Cross-Functional Collaboration: Partner with product managers, data engineers, and stakeholders to define product requirements and deliver high-impact solutions.
- AI Ethics & Governance: Ensure all AI systems adhere to ethical guidelines and regulatory standards regarding bias, fairness, and transparency.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related technical field.
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically focused on Machine Learning and Deep Learning architecture.
- Programming: Expert-level proficiency in Python (PyTorch, TensorFlow, or JAX) and strong knowledge of C++ for high-performance computing.
- Cloud Expertise: Deep understanding of cloud infrastructure (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Mathematical Foundation: Strong background in linear algebra, calculus, probability, and statistics.
- Problem Solving: Demonstrated ability to tackle complex, ambiguous problems and deliver innovative architectural solutions.
- Communication: Exceptional verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.