Artificial Intelligence Specialist

About Seattle Aviation Solutions (SAS)

Position: AI Associate

Key Responsibilities

• Data Engineering & Pipeline Development: Build and maintain scalable, reliable data pipelines and ETL processes to support analytics, reporting, and AI applications.
• AI/ML Enablement: Collaborate with internal stakeholders to identify AI opportunities and develop prototypes that support business functions such as pricing, purchasing optimization, forecasting, and anomaly detection.
• Python Development: Write clean, efficient, modular Python code to support data transformation, automation, web scraping, API integrations, and ML model deployment.
• Data Architecture: Help define and maintain data infrastructure, schemas, and storage systems to ensure high-performance analytics across structured and unstructured datasets.
• Independent Problem Solving: Take ownership of technical challenges, working independently to design and implement end-to-end solutions with minimal oversight.
• Tooling and Infrastructure: Set up and manage tools for data analysis, model development, and experimentation (e.g., Jupyter, Airflow, Docker, Git).
• Collaboration: Work closely with data and IT leadership and other technical team members to translate high-level ideas into deployable code and functional systems.
• R&D: Stay current on AI/ML trends, LLMs, and emerging technologies to help SAS map its AI future and continuously push innovation forward.

Personal Attributes

• Highly intelligent, curious, and motivated by technical challenges.
• Strong problem-solver with a hacker mindset and bias for action.
• Self-directed and capable of managing projects independently from concept to deployment.
• Excellent communication skills and ability to work across technical and non-technical teams.

Experience

Skills

• Strong Python programming expertise.
• Experience with data processing frameworks (e.g., Pandas, NumPy, SQLAlchemy, PySpark).
• Familiarity with cloud environments (e.g., AWS, GCP, or Azure).
• Proficiency with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Redis).
• Experience building and deploying ML models using libraries like scikit-learn, TensorFlow, or PyTorch.
• Comfortable with DevOps tools (Git, Docker, CI/CD pipelines) and working in Linux environments.
• Understanding of REST APIs and third-party data integrations.
• Experience working with large datasets and solving performance bottlenecks.
• Comfortable working within the framework of current tech stack (Snowflake, AWS, Fivetran, Tableau).
• Bonus: Exposure to LLMs, LangChain, Vector Databases (e.g., Pinecone, Weaviate), or NLP applications is highly desirable.

Location

Benefits

• Competitive salary and performance-based incentives
• Comprehensive health insurance
• Opportunity to define and build the AI roadmap of a global aviation company