Job description
NovaTech AI Solutions is seeking a Senior AI Engineer to join our Seattle based R&D and product teams. You will design, implement, and scale AI systems that power our next generation offerings. This is a hands-on role requiring a strong blend of research, software engineering, and collaboration with cross functional teams.
What you will do
- Lead design and implementation of end to end ML models from experimentation to production ready deployment, including data pipelines, feature engineering, and model evaluation
- Develop scalable ML infrastructure and MLOps practices to improve reproducibility, monitoring, and reliability
- Collaborate with product and design teams to translate business needs into AI powered features
- Research and prototype advances in NLP, computer vision, or other AI domains relevant to our products
- Marshal large datasets, curate benchmarks, and ensure data governance and privacy compliance
- Mentor junior engineers and contribute to a culture of high quality and continuous learning
Responsibility
- Lead end to end ML model development from data collection to production deployment
- Design robust data pipelines and feature stores for scalable AI systems
- Collaborate with product teams to align AI capabilities with business goals
- Develop and deploy ML infrastructure for monitoring, logging, and reliability
- Prototype and benchmark new AI approaches with a bias toward impact and practicality
- Mentor engineers and foster a culture of rigorous experimentation and code quality
Qualification
- MS or PhD in computer science, statistics, or a related field with 5+ years of AI experience
- Proven track record deploying ML models in production across NLP or computer vision domains
- Strong programming skills in Python and experience with PyTorch or TensorFlow
- Experience with cloud platforms and MLOps tools including AWS or GCP, Docker, Kubernetes, and CI/CD
- Excellent analytical, problem solving, and communication skills
- Hands on experience with model evaluation, auditing, and bias mitigation
- Commitment to data governance, privacy, and ethical AI practices