3 months ago
San Diego, CA, USAMid Level
Base Salary
$122k - $218k/yr
Responsibilities
- Implement end-to-end generative AI solutions, including model fine-tuning, deployment, and production testing.
- Deploy and operationalize AI workloads on AWS using SageMaker, Lambda, ECS/EKS, and S3.
- Build and maintain AI/ML pipelines using Snowflake for feature engineering and data preprocessing.
- Monitor model performance, troubleshoot issues, and optimize systems for reliability and cost efficiency.
- Research and evaluate generative AI technologies and document models, pipelines, and processes.
- Support AI architecture reviews, code reviews, operationalization planning, and mentoring of junior engineers.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related technical discipline.
- At least 3 years of AI/ML engineering experience, including 1–2 years focused on generative AI or large language models.
- Hands-on experience deploying AI/ML models in cloud environments, preferably AWS.
- Familiarity with Snowflake for AI/ML feature engineering and data integration.
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
- Knowledge of generative AI architectures, MLOps, data pipelines, containerization, monitoring, security, governance, and compliance.
- AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect is preferred but not required; other AI/ML certifications and experience in regulated or data-sensitive industries are advantageous.
Benefits
- Hybrid office arrangement, as indicated by the #LI-HYBRID designation.
- Competitive benefits package including medical, dental, vision, 401K retirement plans, and company match.
- Bonus potential, paid time off, and paid holidays.
- Learning and development support, including 100% support for continued learning.
- No employment sponsorship is offered for this opportunity.
Tech Stack
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