Job description
NovaMind AI Labs is a leading research-driven company delivering scalable AI solutions for enterprise clients. We are seeking a Senior AI Engineer to join our San Francisco team and help build production-grade models that power real-world products.
In this role, you will collaborate with product, data science, and engineering teams to design and deploy end-to-end AI systems, from data ingestion to model monitoring. You’ll work on cutting-edge areas including natural language processing, computer vision, and reinforcement learning, with a strong emphasis on reliability, scalability, and impact.
What we offer: competitive compensation, flexible work arrangements, generous equity, and a culture of experimentation and mentorship. If you’re passionate about turning research into tangible solutions, we want to hear from you.
Responsibility
- Architect, implement, and optimize end-to-end AI systems for production use.
- Collaborate with product and design teams to translate business needs into AI features and define success metrics.
- Build robust ML pipelines including data validation, feature stores, model versioning, A/B testing, and CI/CD for ML (MLOps).
- Research and prototype advanced algorithms in NLP, computer vision, or reinforcement learning and evaluate their applicability to product challenges.
- Deploy models to cloud platforms (AWS, GCP, Azure) with scalable inference services and monitoring.
- Ensure data privacy, security, and responsible AI practices; implement explainability and bias detection.
- Mentor junior engineers and contribute to code reviews, best practices, and cross-functional collaboration.
Qualification
- 5+ years of hands-on experience building and deploying AI/ML models in production environments.
- Bachelor's or Master's degree in computer science, AI, ML, or a related field (PhD a plus).
- Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow.
- Experience with end-to-end ML lifecycle, MLOps, model monitoring, and feature stores.
- Cloud experience (AWS or GCP), containerization (Docker, Kubernetes), and CI/CD for ML.
- Strong problem-solving, communication, and ability to collaborate with cross-functional teams.
- Publications or prior work in AI are a plus; US work authorization required.