Job Description
Join the Visionaries Shaping the Future of Artificial Intelligence.
Nexus Future Systems is at the forefront of the next generation of intelligent systems. We are looking for a visionary Senior AI/ML Engineer to lead the development of scalable, high-impact machine learning models that will redefine industry standards. If you are passionate about pushing the boundaries of what is possible with AI and thrive in a fast-paced, innovative environment, we want to hear from you.
Why Join Us?
- Impactful Work: Directly contribute to projects that shape the future of global industries.
- Innovation First: Work with cutting-edge technologies including LLMs, Generative AI, and Quantum Computing interfaces.
- Competitive Package: Base salary up to $250,000 + Equity + Premium Benefits.
- Growth: Clear path to leadership and technical mastery.
What You Will Do:
As a Senior AI/ML Engineer, you will own the end-to-end lifecycle of our machine learning products. You will bridge the gap between theoretical research and production-grade software, ensuring our solutions are robust, efficient, and ethically aligned.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and algorithms.
- Collaborate with product managers and data scientists to translate business requirements into technical solutions.
- Optimize existing models for latency, throughput, and accuracy in high-volume production environments.
- Mentor junior engineers and conduct technical code reviews to maintain high engineering standards.
- Research and integrate emerging AI technologies (e.g., Transformer architectures, reinforcement learning) into our core stack.
- Ensure data privacy, security, and ethical AI compliance across all projects.
Qualifications
- Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Statistics, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or senior technical role.
- Strong proficiency in Python, PyTorch, and TensorFlow.
- Deep understanding of deep learning architectures and natural language processing (NLP).
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Exceptional problem-solving skills and ability to work in an agile, fast-paced environment.