Job Description
Join the Vanguard of Future Tech
Nexus Systems is on a mission to redefine the landscape of autonomous logistics. We are currently seeking a visionary Senior Machine Learning Engineer to join our elite 'Project 2026' team. This is not just another coding job; it is an opportunity to architect the neural networks that will power the next generation of global supply chain intelligence.
In this high-impact role, you will bridge the gap between theoretical AI and real-world deployment, ensuring our systems are scalable, secure, and ready for the year 2026 and beyond.
Responsibilities
- Architect & Optimize: Design and implement scalable machine learning pipelines and deep learning models for autonomous routing and predictive maintenance systems.
- Research & Innovation: Stay at the forefront of AI research, adapting cutting-edge methodologies (e.g., Transformers, Reinforcement Learning) to solve complex logistical problems.
- Collaborative Engineering: Work closely with cross-functional teams of robotics engineers, data scientists, and product managers to integrate AI models into core infrastructure.
- Deployment & MLOps: Oversee the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training and production deployment via Kubernetes and AWS.
- Performance Tuning: Continuously monitor model accuracy and latency, applying rigorous optimization techniques to ensure real-time decision-making capabilities.
- Mentorship: Guide junior engineers and data scientists, fostering a culture of technical excellence and innovation within the Project 2026 squad.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in machine learning engineering or data science.
- Core Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX; strong understanding of data structures, algorithms, and software design patterns.
- Infrastructure: Extensive experience with cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes).
- Mathematical Fluency: Solid grounding in linear algebra, calculus, and probability/statistics.
- Communication: Ability to translate complex technical concepts into actionable insights for non-technical stakeholders.