Home Job Details
N
Artificial Intelligence 🏢 Full Time ⭐️ Verified

Senior AI Engineer

Northstar AI Labs
Seattle
Salary Estimate
USD 120.000 – USD 180.000
Posting Time
6 Mei 2026
Deadline
6 Mei 2027

Job description

Northstar AI Labs is seeking a Senior AI Engineer to join our Seattle-based team. You will lead the design and delivery of production-ready AI systems that solve real-world problems for enterprise clients. This role blends research, engineering, and product impact in a fast-paced, collaborative environment.

As part of our team, you will work across a modern stack and apply best practices in model development, data engineering, and ML operations to drive business value while maintaining high standards for reliability and ethics.

Responsibility

  • Lead design and development of scalable machine learning and AI systems that power customer-facing products.
  • Collaborate with product managers and data scientists to translate complex business problems into robust ML solutions.
  • Architect end-to-end data pipelines, feature stores, model training, evaluation, and deployment.
  • Optimize models for latency, throughput, cost, and reliability in production environments.
  • Mentor and guide junior engineers; contribute to code reviews, architecture decisions, and best practices.
  • Drive MLops initiatives including CI/CD for models, monitoring, governance, and performance tracking.
  • Stay at the forefront of AI research, run experiments, and communicate results to stakeholders.

Qualification

  • Master's degree in computer science, AI, machine learning, or a related field (PhD a plus).
  • 5+ years of industry experience building and deploying AI/ML systems with a track record of shipped projects.
  • Proficiency in Python and ML frameworks such as PyTorch or TensorFlow, plus experience with scikit-learn.
  • Strong data engineering skills including SQL, Spark, data warehousing, and feature store concepts.
  • Hands-on experience deploying models to production and moderating model performance in cloud environments (AWS, GCP, or Azure).
  • Familiarity with ML Ops tools, containerization (Docker), orchestration (Kubernetes), and monitoring/alerting.
  • Excellent communication, collaboration across product and engineering teams, and ability to mentor others.
  • Publications, patents, or prior research contributions are a plus.

Required Skills

Python PyTorch TensorFlow ML Ops AWS GCP Azure SQL Spark Data Engineering Docker Kubernetes Model Deployment Feature Stores Experimentation

Ready to Take This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

Apply Now

Related Vacancies

Similar job recommendations for you

See All