Job Description
Are you ready to architect the digital landscape of tomorrow?
Nexus 2026 Labs is at the forefront of defining the technological trajectory for the next decade. We are seeking a visionary Lead AI Engineer to spearhead our next-generation research initiatives. In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable production environments, ensuring our solutions are robust, ethical, and ready for the future.
Join a team of elite engineers and data scientists dedicated to solving the complex challenges of the 2026 era. You will have the autonomy to experiment, the resources to innovate, and the impact to shape the future of intelligent systems.
Responsibilities
- Architect & Deploy: Design and implement scalable machine learning pipelines and deep learning models that power our core product suite.
- Research & Innovation: Lead research projects exploring cutting-edge areas such as Generative AI, Reinforcement Learning, and Autonomous Systems.
- Model Optimization: Continuously optimize model performance, latency, and accuracy to handle real-time, high-volume data streams.
- Technical Leadership: Mentor a team of junior engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Collaboration: Work closely with product managers and stakeholders to translate business requirements into technical roadmaps.
- Infrastructure: Oversee the integration of AI models into cloud-native infrastructure (AWS/Azure) ensuring high availability and security.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically focused on AI/ML.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and Scikit-learn. Experience with MLOps tools (Kubernetes, Docker, MLflow) is required.
- Language Models: Strong understanding of Large Language Models (LLMs) and their deployment strategies.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver innovative solutions under tight deadlines.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.