Job Description
Architect the Future of Intelligence
Are you ready to build the systems that will define the year 2026 and beyond? Nexus Future Systems is seeking a visionary Senior AI/ML Engineer to lead our next-generation generative AI initiatives. We are not just predicting trends; we are creating them. Join a team of elite engineers pushing the boundaries of Large Language Models (LLMs), autonomous agents, and ethical AI infrastructure.
In this role, you will bridge the gap between theoretical research and scalable production deployment, ensuring our AI solutions are robust, efficient, and transformative.
Why Join Us?
- Impactful Work: Directly influence the core technology powering the next decade of digital interaction.
- Top-Tier Compensation: Competitive base salary, equity package, and full benefits.
- Future-Proof Environment: Work with cutting-edge frameworks and methodologies before they hit the mainstream market.
Responsibilities
- Model Development: Design, train, and fine-tune large-scale transformer models and diffusion systems for high-performance inference.
- Infrastructure Scalability: Architect distributed training pipelines capable of handling petabyte-scale data processing.
- Optimization: Implement advanced quantization and pruning techniques to reduce latency and operational costs.
- Research Integration: Translate academic breakthroughs from top-tier conferences into production-ready codebases.
- Collaboration: Partner with product teams to define AI strategy and ensure technical feasibility of futuristic features.
- MLOps: Build and maintain CI/CD pipelines for machine learning models, ensuring reproducibility and automated deployment.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field.
- Experience: 5+ years of professional experience in Machine Learning Engineering or Applied AI.
- Core Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX.
- System Design: Deep understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and Kubernetes.
- Innovation: Proven track record of shipping complex AI products to market.
- Communication: Ability to explain complex technical concepts to non-technical stakeholders.