Job Description
We are seeking a visionary Senior AI Research Engineer to join our elite team at Nexus AI Solutions. In this pivotal role, you will architect the next generation of machine learning models that will power our flagship products, influencing industries from healthcare to autonomous logistics. We are looking for a candidate who not only possesses deep technical expertise but also a passion for solving complex problems with elegant, scalable solutions.
Your work will involve pushing the boundaries of Deep Learning and Natural Language Processing (NLP). You will collaborate directly with our Principal Scientists and Product Managers to define technical roadmaps and ensure our algorithms are not only state-of-the-art but also production-ready and efficient. If you thrive in a fast-paced, innovative environment and want to build AI that truly matters, we want to hear from you.
At Nexus AI Solutions, we offer a competitive compensation package, comprehensive health benefits, and a dynamic culture that encourages continuous learning and experimentation.
Responsibilities
- Design, train, and optimize state-of-the-art deep learning models, specifically focusing on Transformer architectures and generative AI.
- Collaborate with data engineering teams to preprocess large-scale datasets and implement robust data pipelines.
- Deploy models to cloud environments (AWS/Azure) using containerization technologies (Docker, Kubernetes) and MLOps frameworks.
- Conduct rigorous experimentation and hyperparameter tuning to improve model accuracy and reduce inference latency.
- Mentor junior engineers and data scientists, fostering a culture of technical excellence and knowledge sharing.
- Stay abreast of the latest research in AI/ML and contribute to internal technical blogs and conference presentations.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- 5+ years of professional experience in machine learning, deep learning, or a related research role.
- Expert proficiency in Python, PyTorch, TensorFlow, and Scikit-learn.
- Strong understanding of mathematical foundations, including linear algebra, calculus, and probability theory.
- Experience with distributed computing frameworks (Spark, Hadoop) and cloud-based AI services.
- Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, ACL) or shipping high-impact production models.