Job description
Join Lumina AI Labs, a leading innovator in artificial intelligence research and deployment, located in the heart of San Francisco. We build scalable, ethically-aligned AI systems that power next-generation products for Fortune 500s and startups alike. This role leads cross-functional initiatives, mentors engineers, and shapes our AI strategy.
As a Lead AI Engineer, you will own end-to-end model development—from ideation to production—shipping robust, scalable solutions that solve real-world problems. You will collaborate with product, data science, and engineering teams to translate ambitious business goals into tangible AI capabilities, and you will drive responsible AI practices, model governance, and operational excellence in a fast-paced environment.
What you bring: a track record of shipping production-grade AI systems, exceptional software engineering discipline, and a passion for turning research into impact. We offer a collaborative, inclusive culture with hybrid work options in San Francisco.
Responsibility
- Lead end-to-end AI model development from data collection and feature engineering to training, evaluation, and production deployment, with robust monitoring and retraining workflows.
- Collaborate with product, design, and data science teams to transform complex problems into scalable AI solutions that drive business outcomes.
- Mentor and grow a team of AI researchers and engineers; establish engineering best practices, code reviews, and scalable software design.
- Own MLOps infrastructure, CI/CD for ML pipelines, model monitoring, alerting, and incident response to ensure reliability at scale.
- Champion responsible AI: fairness, privacy, security, interpretability, and governance in all projects.
- Partner with platform and cloud teams to deploy models on distributed resources with cost and performance optimization.
- Communicate findings and roadmaps to stakeholders; publish research internally and contribute to open-source or patents where applicable.
Qualification
- Master's or PhD in Computer Science, Electrical Engineering, Mathematics, or a related field; 5+ years of hands-on AI/ML engineering experience.
- Proficiency in Python and strong software engineering practices; experience with ML frameworks TensorFlow and PyTorch and high-quality code delivery.
- Experience with cloud platforms AWS, GCP, or Azure and MLOps tools Kubeflow, MLflow, Airflow; containerization with Docker and Kubernetes.
- Expertise in NLP, Computer Vision, or Reinforcement Learning; strong data modeling and feature engineering skills.
- Demonstrated ability to design, implement, and maintain production-grade ML systems; experience with model governance, evaluation, bias mitigation, and privacy considerations.
- Excellent communication, leadership, and collaboration skills; ability to mentor teams and influence cross-functional stakeholders.
- Track record of delivering impact in fast-paced environments; publications or patents are a plus.