Job Description
The Future is Now, and We Need You to Build It.
Nexus Future Labs is at the forefront of the next technological revolution. We are seeking a visionary Senior AI Engineer to join our elite research and development team. As we prepare for the 2026 AI landscape, you will be responsible for architecting robust, scalable, and ethical artificial intelligence systems that redefine human-computer interaction.
In this role, you won't just write code; you will define the standards for the next generation of intelligent applications. If you are passionate about Generative AI, Large Language Models (LLMs), and solving complex problems with data, we want to hear from you.
Why Join Us?
- Work with cutting-edge technology in a forward-thinking environment.
- Competitive compensation and equity packages.
- Flexible remote-first culture with a focus on innovation.
Responsibilities
- Model Architecture & Development: Design, train, and deploy state-of-the-art Machine Learning and Deep Learning models, with a focus on LLMs and generative AI frameworks.
- Research & Innovation: Conduct advanced research to stay ahead of industry trends, specifically targeting advancements relevant to the 2026 technological horizon.
- System Optimization: Optimize inference and training pipelines to ensure scalability, speed, and cost-efficiency in production environments.
- Data Strategy: Lead the data engineering team in curating high-quality datasets and implementing robust data governance protocols.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and designers to translate complex technical requirements into user-centric AI solutions.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: Minimum of 5+ years of professional experience in AI/ML engineering, with a proven track record of shipping production-ready models.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Kubeflow, MLflow, Docker, Kubernetes).
- AI Expertise: Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Problem Solving: Exceptional ability to tackle ambiguous problems and derive actionable insights from unstructured data.
- Communication: Strong verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.