Job Description
Are you ready to architect the next generation of intelligent systems?
At Nexus Future Labs, we are building the infrastructure for the future. As a Senior AI/ML Engineer, you will be at the forefront of innovation, designing and deploying state-of-the-art machine learning models that power our global platform. We are looking for a visionary engineer who thrives in a fast-paced environment and is passionate about solving complex problems with data-driven solutions.
At Nexus Future Labs, we are building the infrastructure for the future. As a Senior AI/ML Engineer, you will be at the forefront of innovation, designing and deploying state-of-the-art machine learning models that power our global platform. We are looking for a visionary engineer who thrives in a fast-paced environment and is passionate about solving complex problems with data-driven solutions.
Responsibilities
- Model Development & Deployment: Design, train, and deploy scalable machine learning models and pipelines using Python and modern deep learning frameworks (TensorFlow, PyTorch).
- Research Implementation: Stay current with the latest advancements in AI research and implement novel algorithms to improve product performance.
- System Optimization: Continuously monitor model performance, optimize infrastructure for latency and cost efficiency, and ensure high availability.
- Collaboration: Partner with cross-functional teams including data scientists, backend engineers, and product managers to define technical requirements.
- Mentorship: Provide technical guidance to junior engineers, conduct code reviews, and foster a culture of continuous learning.
- Production Support: Troubleshoot complex issues in production environments and ensure robust data governance practices.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or Artificial Intelligence.
- Technical Proficiency: Strong proficiency in Python, SQL, and experience with cloud platforms (AWS, GCP, or Azure).
- Frameworks: Deep knowledge of machine learning libraries such as Scikit-learn, Pandas, and experience with model serving tools.
- Communication: Excellent verbal and written communication skills with the ability to translate complex technical concepts for diverse audiences.