Job Description
We are seeking a visionary Senior AI/ML Engineer to join Nexus 2026 Dynamics, a pioneer in next-generation artificial intelligence solutions. As we build the technological infrastructure for the future, we are looking for a technical expert to architect scalable machine learning models and drive innovation in generative AI.
In this role, you will lead the development of state-of-the-art AI systems designed to solve complex problems in 2026 and beyond. You will collaborate with cross-functional teams to integrate AI capabilities into our core products, ensuring ethical, efficient, and impactful technology.
Why Join Us?
- Work on cutting-edge projects shaping the future of AI.
- Competitive salary and equity package.
- Flexible remote-first culture with a hub in San Francisco.
- Opportunity to define the roadmap for AI in the enterprise sector.
Responsibilities
- Architect and Deploy AI Models: Design, train, and deploy advanced machine learning and deep learning models (e.g., LLMs, Computer Vision) for production environments using Python and modern frameworks.
- Optimization & Scalability: Optimize model inference and training pipelines for speed, accuracy, and cost-efficiency on cloud infrastructure (AWS/GCP/Azure).
- Data Engineering: Design robust data pipelines and data strategies to feed high-quality training data into models, ensuring data integrity and privacy compliance (GDPR/CCPA).
- MLOps Implementation: Establish and maintain MLOps workflows, including CI/CD for models, automated monitoring, and retraining strategies.
- Cross-Functional Collaboration: Partner with product managers and engineers to translate business requirements into technical AI solutions.
- Ethical AI: Ensure AI systems are fair, transparent, and unbiased, adhering to the highest standards of AI ethics.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field (PhD preferred).
- Experience: 5+ years of professional experience in AI/ML engineering, with a strong portfolio of deployed models.
- Programming: Expert-level proficiency in Python (PyTorch, TensorFlow, Scikit-learn) and SQL.
- Infrastructure: Deep understanding of cloud platforms (AWS, GCP) and containerization technologies (Docker, Kubernetes).
- Machine Learning: Proven track record in Natural Language Processing (NLP) or Computer Vision is a plus.
- Soft Skills: Strong problem-solving skills, excellent communication abilities, and the ability to mentor junior engineers.