Overview
Skills
Job Details
Job Title : Principal AI/ML Engineer
Location: Seattle, WA
Role Overview
We are looking for a highly accomplished Principal AI/ML Engineer to lead the design, development, and deployment of next-generation AI solutions. This role requires a visionary technical leader with deep expertise in Generative AI, LLMs, MLOps, and advanced ML architectures. You will define the technical strategy, mentor engineering teams, and drive innovation across enterprise AI initiatives.
Key Responsibilities
AI/ML Architecture & Solution Design
- Architect scalable AI/ML frameworks, platforms, and system designs aligned with enterprise needs.
- Develop standards, best practices, and reusable components for high-performance AI systems.
End-to-End Model Lifecycle
- Lead the full ML lifecycle including data preparation, feature engineering, model training, optimization, deployment, and ongoing monitoring.
- Ensure model performance, accuracy, and reliability at scale.
MLOps & Engineering Excellence
- Build and optimize end-to-end MLOps pipelines using industry-leading tools.
- Enable CI/CD for ML workflows and production-grade automation of training and inference systems.
Leadership & Team Development
- Mentor senior engineers and guide cross-functional technical teams toward building impactful AI products.
- Foster a culture of innovation, technical rigor, and continuous improvement.
Generative AI & Innovation
- Lead initiatives in LLM fine-tuning, Retrieval-Augmented Generation (RAG), embeddings, and vector search technologies.
- Evaluate emerging AI trends and technologies to accelerate organizational innovation.
Governance, Security & Ethics
- Ensure compliance with AI governance, fairness, bias mitigation, and responsible AI principles.
- Define policies for secure, safe, and ethical AI practices.
Strategic Business Alignment
- Collaborate with business, product, and executive teams to align AI programs with organizational priorities.
- Translate complex technical concepts into actionable business strategies.
Required Skills & Experience
Technical Expertise
- Strong proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and Transformer architectures.
- Hands-on experience with LLM fine-tuning, RAG, and vector databases such as FAISS and Pinecone.
MLOps & Cloud Platforms
- Expertise with MLflow, Airflow, Docker, Kubernetes, and modern ML automation pipelines.
- Experience with cloud ML platforms such as AWS SageMaker, Google Cloud Platform Vertex AI, or Azure ML.
Data & Governance
- Strong understanding of data engineering, model governance, AI fairness, and ethical AI practices.
Leadership & Communication
- Excellent communication, stakeholder management, and ability to influence technical and business leaders at all levels.
- Proven experience leading large-scale AI/ML initiatives and mentoring engineering teams.