Job Description
We are looking for a visionary Senior AI Engineer to architect the intelligent systems of 2026 and beyond.
At Nexus Future Technologies, we are not just building tools for today; we are defining the roadmap for the next decade. As part of our elite Research & Development team, you will lead the creation of autonomous agents and generative AI models that will redefine user interaction. You will operate at the intersection of deep learning, distributed systems, and futuristic UI/UX design.
If you are passionate about pushing the boundaries of what is possible in AI and want to leave a legacy in the technology landscape of 2026, we want to hear from you.
Responsibilities
- Architect Scalable AI Systems: Design and implement robust, high-performance machine learning pipelines capable of handling petabyte-scale data.
- Pioneering Research: Lead the research and development of next-generation Large Language Models (LLMs) and generative vision algorithms.
- Model Optimization: Reduce inference latency and optimize model accuracy for real-time, edge-deployed applications.
- Cross-Functional Leadership: Collaborate with product managers, designers, and engineers to translate complex AI concepts into intuitive user experiences.
- Technical Mentorship: Foster a culture of innovation by mentoring junior engineers and conducting code reviews to ensure best practices in AI development.
- Deployment & DevOps: Manage the end-to-end deployment of models on cloud infrastructure (AWS/GCP) using containerization and CI/CD pipelines.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: 5+ years of professional experience in AI/ML engineering, specifically in NLP, Computer Vision, or Reinforcement Learning.
- Programming: Strong proficiency in Python, PyTorch, or TensorFlow, with deep knowledge of C++ for performance optimization.
- Big Data: Proven experience working with large-scale data processing frameworks like Apache Spark or Hadoop.
- Cloud Expertise: Solid understanding of cloud services (AWS, GCP, or Azure) and container orchestration (Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex, unstructured problems and deliver innovative solutions under tight deadlines.