Job Description
Are you ready to define the technological landscape of 2026? Nexus Future Systems is looking for a visionary Senior AI/ML Engineer to lead our next-generation artificial intelligence initiatives. We are not just building software; we are architecting the future of human-machine interaction.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable production environments. You will work on cutting-edge projects involving Generative AI, Computer Vision, and Predictive Analytics. If you possess a deep understanding of neural networks and want to influence the trajectory of the industry, this is your opportunity to excel.
Why Join Us?
- Work on breakthrough technology that will define the next decade.
- Competitive compensation package with equity options.
- Flexible remote-first culture with access to premium tech hubs.
- Continuous learning budget and access to the latest hardware.
Responsibilities
- Design, develop, and deploy scalable machine learning models using Python, TensorFlow, and PyTorch.
- Lead the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model monitoring and retraining.
- Collaborate with cross-functional product teams to translate complex business requirements into robust AI solutions.
- Optimize deep learning algorithms for high-performance inference on edge devices and cloud infrastructure.
- Stay ahead of industry trends in AI, including Large Language Models (LLMs), autonomous agents, and ethical AI.
- Conduct rigorous A/B testing and performance analysis to ensure model reliability and business impact.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent significant experience).
- 5+ years of professional experience designing, implementing, and maintaining machine learning systems in production.
- Proficiency in programming languages such as Python, C++, and SQL.
- Strong foundation in statistics, probability theory, and linear algebra.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).