Job Description
We are seeking a visionary Senior AI/ML Engineer to pioneer the technological landscape of 2026. At Nexus Future Labs, we are not just building software; we are architecting the future of human-machine interaction. If you have a passion for pushing the boundaries of Generative AI, Large Language Models, and Autonomous Agents, we want to hear from you.
In this role, you will lead a high-impact team in developing next-generation AI solutions that redefine industry standards. You will work at the intersection of research and production, ensuring our models are not only state-of-the-art but also ethical, scalable, and secure.
Responsibilities
- Architect & Deploy: Design, train, and deploy cutting-edge machine learning models and deep learning architectures at scale.
- Research Leadership: Lead internal research initiatives focusing on LLM optimization, computer vision, and reinforcement learning.
- Infrastructure: Build and maintain robust MLOps pipelines using Kubernetes, AWS, and Docker for seamless model deployment.
- Collaboration: Partner with product managers and data scientists to translate complex business requirements into technical AI solutions.
- Mentorship: Guide a team of junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Performance Optimization: Continuously monitor, evaluate, and improve model performance and inference latency.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with a strong portfolio of shipped products.
- Tools: Proficiency in Python, TensorFlow, PyTorch, and scikit-learn.
- MLOps: Experience with cloud platforms (AWS/GCP/Azure), CI/CD, and containerization technologies.
- Language: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Proven track record of solving complex, unstructured problems in high-pressure environments.