- Company Name
- Qodea
- Job Title
- Principal Machine Learning Engineer
- Job Description
-
**Job Title:** Principal Machine Learning Engineer
**Role Summary:**
Lead the design, architecture, and delivery of scalable data pipelines and machine‑learning systems. Drive cross‑functional initiatives to integrate advanced AI (semantic understanding, NLP, LLMs) for data quality, enrichment, and product linking. Mentor a diverse engineering team and set best practices for performance, reliability, and observability.
**Expectations:**
- Architect end‑to‑end data and ML pipelines for complex, high‑volume datasets.
- Own technical direction and influence organization‑wide engineering standards.
- Mentor and elevate team skill sets across ML, data engineering, and infrastructure.
- Deliver production‑ready solutions that meet stringent quality and latency requirements.
**Key Responsibilities:**
- Design and evolve large‑scale distributed ETL and ML back‑end systems (e.g., Beam, Pub/Sub).
- Implement data ingestion, transformation, quality checks, enrichment, and canonical linking.
- Build and maintain robust APIs (REST/GraphQL) and cloud services (GCP preferred).
- Establish observability, monitoring, CI/CD, and deployment pipelines (Kubernetes, Docker).
- Develop frameworks for offline and online evaluation of data quality and model performance.
- Champion coding standards, data governance, and ML system design excellence.
- Stay current with AI/ML trends and bring proven innovations into production.
**Required Skills:**
- 10+ years in designing large‑scale distributed data/ML systems.
- Expertise in ETL pipeline design, optimization, and data processing frameworks (Apache Beam, Pub/Sub, Spark).
- Proficiency in Python and Scala; familiarity with Node.js or Go.
- Strong command of SQL & NoSQL databases, data warehousing, and API development.
- Experience with cloud environments (GCP), Kubernetes, Docker, CI/CD, observability.
- Proven leadership in cross‑functional teams and technical mentorship.
- Excellent communication for aligning diverse stakeholders.
**Required Education & Certifications:**
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
- Relevant certifications (e.g., GCP Professional Data Engineer, AWS Big Data Specialty, or equivalent) preferred.