AI Engineer
Cayuse, LLC
1 month ago
Role details
Contract type
Temporary contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Compensation
$ 62KJob location
Remote
Tech stack
A/B testing
Artificial Intelligence
Azure
Big Data
Databases
ETL
Data Visualization
Python
Machine Learning
Natural Language Processing
NumPy
Unstructured Data
PyTorch
Prompt Engineering
Pandas
Data Lake
Text Analysis
Spacy
Data Pipelines
Job description
- Conduct monthly fine-tuning of AI models based on customer usage and feedback.
- Continuously monitor AI outputs for accuracy, fairness, and safety alignment.
- Develop strategies for handling bias, hallucinations, and compliance issues in AI-generated results.
- Collaborate with engineers to integrate refined models into production environments.
- Perform weekly output refinement, including prompt engineering and embedding updates.
- Design and maintain workflows for AI pipelines and evaluation benchmarks.
- Ensure AI compliance with organizational, ethical, and regulatory standards (e.g., GDPR, SOC2, Responsible AI principles).
- Leverage and optimize Azure AI services (OpenAI, Cognitive Search, Document AI, Vector DB, etc.).
- Analyze datasets to extract insights, build predictive models, and support data-driven decision-making.
- Design and execute experiments (A/B testing, model evaluation, statistical validation) to improve AI reliability and performance.
- Design, manage, and optimize ETL pipelines for structured and unstructured data ingestion.
- Work with big data platforms and Azure Data Lakes to ensure scalable storage, processing, and retrieval.
Requirements
- Strong background in Machine Learning, NLP, and Data Science.
- Hands-on experience with Azure AI services (OpenAI, Azure AI Search, Cognitive Search, Document AI).
- Proficient in Python for AI/ML development, automation, and data pipelines.
- Practical experience with spaCy, Pandas, NumPy, PyTorch, and advanced text analytics.
- Knowledge of embeddings, RAG pipelines, vector databases, and fine-tuning methodologies.
- Strong foundation in statistical modeling, A/B testing, and data visualization.
- Experience with ETL workflows, big data processing, and Azure Data Lakes.
- Familiarity with compliance frameworks and AI governance best practices.
- Strong analytical, problem-solving, and critical-thinking skills.
