Job Description
Join the Future of Intelligence
Nexus Future Labs is pioneering the next generation of Generative AI and Large Language Models (LLMs). We are looking for a visionary Senior AI Engineer to lead the development of scalable, ethical, and high-performance AI systems that will define the industry standard for 2026 and beyond.
In this role, you will work at the intersection of deep learning, software engineering, and product innovation. You will be responsible for designing end-to-end machine learning pipelines, optimizing model inference for edge devices, and collaborating with cross-functional teams to deploy cutting-edge solutions into production environments.
If you are passionate about building AI that transforms industries and want to work with the best minds in the tech sector, we want to hear from you.
Nexus Future Labs is pioneering the next generation of Generative AI and Large Language Models (LLMs). We are looking for a visionary Senior AI Engineer to lead the development of scalable, ethical, and high-performance AI systems that will define the industry standard for 2026 and beyond.
In this role, you will work at the intersection of deep learning, software engineering, and product innovation. You will be responsible for designing end-to-end machine learning pipelines, optimizing model inference for edge devices, and collaborating with cross-functional teams to deploy cutting-edge solutions into production environments.
If you are passionate about building AI that transforms industries and want to work with the best minds in the tech sector, we want to hear from you.
Responsibilities
- Architect and implement complex machine learning models, specifically focusing on LLMs and Computer Vision applications.
- Design and optimize data pipelines for large-scale training and inference using cloud-native technologies (AWS, GCP, or Azure).
- Collaborate with product managers and engineers to translate technical requirements into robust, scalable software solutions.
- Mentor junior data scientists and engineers, fostering a culture of continuous learning and innovation.
- Ensure model reliability, fairness, and interpretability while adhering to ethical AI guidelines.
- Stay abreast of the latest research in Deep Learning and implement novel techniques to improve model performance.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience).
- 5+ years of professional experience in AI/ML engineering, with at least 2 years focused on large-scale model deployment.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Extensive experience with MLOps tools (Kubeflow, MLflow, Airflow) and containerization (Docker, Kubernetes).
- Familiarity with vector databases (Pinecone, Milvus) and RAG architectures.
- Excellent problem-solving skills and the ability to work in a fast-paced, agile environment.