Job Description
Are you ready to architect the future of intelligent systems? Nexus Future Tech is seeking a visionary Senior AI Engineer to lead our groundbreaking 'Project 2026' initiative. We are building the next generation of autonomous agents and generative models that will redefine how businesses interact with the digital world.
In this role, you won't just be maintaining existing systems; you will be laying the foundation for the technological landscape of the year 2026 and beyond. If you thrive in fast-paced environments and are passionate about pushing the boundaries of Machine Learning, we want to meet you.
Why Join Us?
- Work on cutting-edge Generative AI and Large Language Models.
- Competitive equity and performance-based bonuses.
- Flexible remote-first culture with quarterly team retreats.
Apply today to be part of the team shaping the future.
Responsibilities
- Architect Scalable AI Systems: Design and implement robust machine learning pipelines capable of handling high-throughput data streams and real-time inference.
- Model Optimization: Fine-tune and optimize neural network architectures for speed, accuracy, and resource efficiency.
- Research & Development: Stay at the forefront of AI research, implementing state-of-the-art techniques (e.g., Transformers, Diffusion Models) into production code.
- Collaboration: Partner with data scientists and software engineers to integrate AI models into broader product ecosystems.
- Mentorship: Guide junior engineers and conduct technical code reviews to ensure high standards across the team.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: Minimum 5+ years of professional experience in Machine Learning engineering, preferably in a high-scale production environment.
- Technical Skills: Deep proficiency in Python, PyTorch, or TensorFlow; experience with cloud platforms (AWS, GCP, or Azure).
- Infrastructure: Strong understanding of containerization (Docker, Kubernetes) and MLOps practices.
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and derive data-driven solutions.