Job Description
Shape the Future of Intelligence.
Nexus Dynamics is pioneering the next generation of autonomous AI systems. We are looking for a visionary Senior AI/ML Engineer to join our elite team in San Francisco. If you are passionate about pushing the boundaries of Generative AI, Deep Learning, and Large Language Models, we want to hear from you.
In this pivotal role, you will not only build cutting-edge models but also define the architectural standards for our AI infrastructure. You will work in a fast-paced environment where innovation is the currency and problem-solving is the daily routine.
Responsibilities
- Model Development: Lead the research, design, and implementation of advanced machine learning algorithms, specifically focusing on LLMs and multimodal AI.
- Infrastructure: Architect scalable and efficient data pipelines and training infrastructure on cloud platforms (AWS/GCP/Azure).
- Deployment: Oversee the deployment of models into production environments, ensuring high availability, low latency, and fault tolerance.
- Collaboration: Partner with product managers and engineers to translate complex business requirements into robust technical solutions.
- Ethics & Safety: Implement best practices for model interpretability, fairness, and bias mitigation to ensure responsible AI.
- Mentorship: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Statistics, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML engineering, with at least 2 years in a leadership or senior technical role.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX; extensive experience with deep learning frameworks.
- Cloud & Tools: Strong familiarity with cloud services, containerization (Docker/Kubernetes), and MLOps tools (MLflow, Kubeflow).
- Problem Solving: Proven track record of solving complex data problems and optimizing model performance.