Job Description
Are you ready to architect the future of predictive intelligence?
Nexus Systems is pioneering the Project 2026 initiative—a revolutionary next-generation AI ecosystem designed to redefine enterprise scalability and decision-making capabilities. We are seeking a visionary Senior Machine Learning Engineer to lead the core development of our proprietary neural engines. In this role, you will not just write code; you will shape the infrastructure that powers the next decade of technological advancement.
Why Join Us?
- Impactful Work: Build foundational systems used by Fortune 500 companies to optimize supply chains and financial forecasting.
- Innovation: Work with cutting-edge technologies including Quantum-Ready algorithms and Federated Learning.
- Culture: A collaborative, high-performance environment that rewards curiosity and technical excellence.
If you are passionate about pushing the boundaries of what's possible in 2026 and beyond, we want to hear from you.
Responsibilities
- Architect & Deploy: Lead the end-to-end development and deployment of scalable machine learning models for the Project 2026 platform.
- Optimization: Drive performance tuning and resource optimization to ensure low-latency inference in high-volume environments.
- Research: Stay at the forefront of AI research, evaluating and integrating new methodologies (e.g., Transformer architectures, Reinforcement Learning) into production systems.
- Collaboration: Partner with cross-functional teams of data scientists, product managers, and backend engineers to translate business requirements into technical specifications.
- Mentorship: Mentor junior engineers and conduct code reviews to maintain high standards of engineering excellence and code quality.
- Infrastructure: Design and maintain CI/CD pipelines and MLOps workflows to automate model training and deployment cycles.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field (PhD preferred).
- Experience: 7+ years of professional experience in machine learning engineering, with at least 3 years in a senior or lead role.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and SQL. Experience with distributed systems (Kubernetes, Apache Spark) is highly desirable.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-pressure environments.
- Agile: Experience working in Agile/Scrum environments with a focus on rapid iteration and delivery.