Job Description
Are you ready to architect the future of technology? Nexus 2026 is looking for a visionary Senior AI/ML Engineer to lead our cutting-edge initiatives. As we prepare for the next generation of artificial intelligence, we need a technical leader who can bridge the gap between theoretical research and scalable production systems.
In this role, you will be at the forefront of innovation, designing robust machine learning models that redefine user experiences. Join a team that values creativity, technical excellence, and the relentless pursuit of progress.
Responsibilities
- Architect and Deploy: Design, train, and deploy advanced machine learning models, including Large Language Models (LLMs) and generative AI systems, ensuring high performance and scalability.
- Research & Development: Stay ahead of the curve by researching the latest advancements in AI, computer vision, and natural language processing to integrate novel solutions into our product suite.
- Model Optimization: Continuously optimize existing models for speed, accuracy, and cost-efficiency, implementing best practices in MLOps and model governance.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous learning within the engineering team.
- Stakeholder Collaboration: Partner with product managers and cross-functional teams to translate complex technical requirements into actionable development roadmaps.
- Production Monitoring: Implement robust monitoring and alerting systems to track model performance in production, ensuring reliability and quick resolution of any drift issues.
Qualifications
- Experience: 5+ years of professional experience in software engineering or machine learning, with a strong focus on AI/ML development.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with cloud platforms (AWS, GCP, or Azure).
- Education: BS, MS, or PhD in Computer Science, Statistics, Mathematics, or a related technical field.
- Soft Skills: Excellent problem-solving abilities, strong communication skills, and the ability to work effectively in a fast-paced, agile environment.
- AI Expertise: Deep understanding of deep learning architectures, neural networks, and data preprocessing techniques.
- Tooling: Experience with version control (Git), CI/CD pipelines, and containerization (Docker, Kubernetes).