Job Description
We are building the infrastructure for tomorrow. Nexus Future Labs is seeking a visionary Senior AI Engineer to spearhead our next-generation generative AI initiatives. If you are passionate about architecting systems that define the future of technology, we want to meet you.
In this pivotal role, you will bridge the gap between theoretical AI research and production-grade deployment. You will be instrumental in deploying Large Language Models (LLMs) and autonomous agents capable of solving complex, real-world problems by the year 2026 and beyond.
Why join us?
We offer top-tier equity, a fully remote-first culture, and the freedom to experiment with cutting-edge tech stacks. You will work directly with C-level executives to shape the roadmap of our AI platform.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement scalable, high-performance machine learning pipelines focused on Generative AI and Reinforcement Learning.
- Model Optimization: Fine-tune and optimize state-of-the-art models (e.g., GPT-4, Llama 3) for latency, cost-efficiency, and accuracy in production environments.
- R&D Leadership: Lead internal research initiatives to explore emerging technologies, including Quantum AI and Neural Interfaces.
- Collaboration: Partner with product teams to translate complex AI capabilities into intuitive user experiences.
- MLOps Implementation: Establish robust CI/CD pipelines for machine learning models, ensuring continuous integration and deployment.
- Code Review & Mentorship: Mentor junior engineers and conduct rigorous code reviews to maintain high engineering standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years dedicated to Machine Learning or AI.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and LangChain.
- Architecture: Deep understanding of distributed systems, microservices, and cloud-native architecture (AWS/GCP).
- Problem Solving: Proven track record of solving complex algorithmic problems and improving model performance metrics.
- Communication: Excellent ability to communicate complex technical concepts to non-technical stakeholders.