Job Description
Shape the Future of 2026 with Nexus 2026 Solutions. We are at the forefront of technological innovation, building the next generation of intelligent systems. We are looking for a visionary Senior AI & Machine Learning Engineer to join our elite team and drive the development of scalable, production-ready AI solutions.
In this pivotal role, you will not just use existing tools; you will help define the standards for the year 2026 and beyond. You will be responsible for architecting deep learning models, optimizing large-scale data pipelines, and ensuring our AI systems are robust, ethical, and impactful.
What You Will Do:
- Lead the end-to-end development of machine learning models and deep learning architectures.
- Research and implement cutting-edge algorithms in Natural Language Processing (NLP) and Computer Vision.
- Collaborate with product and engineering teams to deploy models into high-traffic production environments.
- Drive best practices in MLOps, including model versioning, monitoring, and automated retraining.
- Ensure data privacy, security, and ethical compliance across all AI initiatives.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence.
Join us in building the intelligence layer of the digital world.
Responsibilities
- Design and implement scalable machine learning pipelines and deep learning architectures.
- Research and integrate the latest advancements in AI, focusing on NLP and Computer Vision.
- Optimize models for low-latency, high-throughput inference in production environments.
- Collaborate with cross-functional teams to translate business requirements into technical AI solutions.
- Ensure data integrity, model explainability, and ethical AI compliance.
- Conduct code reviews and mentor junior data scientists and engineers.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of professional experience in machine learning, deep learning, or data science.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
- Deep understanding of statistics, probability, and linear algebra.
- Excellent problem-solving skills and ability to work in a fast-paced, agile environment.