Job Description
At Nexus Future Labs, we are pioneering the next generation of intelligent systems. We are currently seeking a visionary Senior AI/ML Engineer to spearhead Project 2026, our ambitious initiative to develop self-evolving neural architectures capable of solving complex global challenges.
In this role, you will bridge the gap between theoretical research and scalable production systems. You will work in a high-performance environment that values innovation, code quality, and the rapid deployment of cutting-edge models. If you are passionate about the future of Artificial General Intelligence and want to build systems that matter, we want to meet you.
Why Join Us?
We offer competitive compensation, equity packages, and a remote-first culture that empowers you to work from anywhere in the US. You will have the autonomy to design systems that redefine the industry standard.
Responsibilities
- Design, train, and deploy state-of-the-art Machine Learning and Deep Learning models for large-scale applications.
- Optimize existing AI pipelines for latency, throughput, and memory efficiency using Rust and C++.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to define technical requirements.
- Implement robust MLOps strategies to ensure model reproducibility, monitoring, and automated retraining pipelines.
- Research and integrate the latest advancements in Natural Language Processing (NLP) and Computer Vision.
- Conduct code reviews and mentor junior engineers to foster a culture of technical excellence.
Qualifications
- Master’s or PhD degree in Computer Science, Mathematics, or a related technical field.
- Minimum of 5+ years of experience in Machine Learning engineering, with a strong portfolio of deployed models.
- Expert proficiency in Python (PyTorch, TensorFlow, JAX) and deep understanding of model architecture.
- Strong experience with distributed computing frameworks (Apache Spark, Kubernetes) and cloud platforms (AWS, GCP, Azure).
- Experience with vector databases (Pinecone, Milvus) and RAG (Retrieval-Augmented Generation) architectures.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.