- Company Name
- OSI Engineering
- Job Title
- AI Data & Python Tools Engineer for a well-known consumer device company in Austin, TX
- Job Description
-
**Job title:** AI Data & Python Tools Engineer
**Role Summary:**
Design, develop, and deploy production‑ready AI applications and data pipelines using Python, React, and modern ML frameworks. Lead rapid prototyping, performance tuning, and scalable cloud deployment. Integrate Model Context Protocol (MCP) systems and maintain end‑to‑end technical documentation.
**Expectations:**
- Deliver production‑grade AI tools on a fast schedule.
- Collaborate with product, engineering, and data science teams to solve complex problems.
- Maintain code quality through reviews, documentation, and solid testing practices.
- Operate within a cloud‑native, containerized environment.
**Key Responsibilities:**
1. Build full‑stack AI applications with Python (backend) and React (frontend).
2. Design and orchestrate end‑to‑end data pipelines; stream, process, and transform data.
3. Train, validate, and deploy ML models; perform rigorous evaluation and monitoring.
4. Implement MCP server components and integrate with AI assistants and vector databases.
5. Provision and manage cloud resources (AWS/GCP/Azure) and big‑data platforms (Spark, Kafka).
6. Create and maintain data warehouses (Snowflake, BigQuery, Redshift) and data lakes.
7. Apply containerization (Docker, Kubernetes) and infrastructure‑as‑code for scalable deployments.
8. Contribute to API design, UX/UI for internal tools, and MLOps pipelines (Airflow).
**Required Skills:**
- Strong Python fundamentals; experience building backend services and data processing pipelines.
- Familiarity with ML/DL frameworks: TensorFlow, PyTorch, scikit‑learn.
- Knowledge of LLMs, vector databases, retrieval systems, and MCP integration.
- Cloud expertise (AWS, GCP, or Azure) and big‑data technologies (Spark, Kafka).
- Data warehouse and lake skills: Snowflake, BigQuery, Redshift.
- Containerization (Docker, Kubernetes) and IaC.
- Proficient in API development; basic front‑end experience with React (preferred).
- Understanding of MLOps practices (Airflow) and real‑time analytics.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field.
- Relevant cloud certification (AWS/Azure/GCP) is a plus.