Artificial Intelligence Engineer

Overview

*AI And ML Solution Design & Architecture*

• Design end‑to‑end AI/ML solutions using GCP services.
• Define data, training, inference and deployment architectures that meet security, scalability and reliability standards.
• Deliverables: GCP architecture docs, approved technical designs, reusable patterns.

*Model Development, Training & Evaluation (Vertex AI)*

• Develop, train, fine‑tune and evaluate ML/DL models using Vertex AI; implement feature engineering and preprocessing.
• Perform validation, bias checks and benchmarking.
• Deliverables: trained/validated models, experiment tracking, reproducible training artifacts.

*Data Integration & Feature Engineering (BigQuery)*

• Source and prepare training/inference data using BigQuery and cloud pipelines; design feature stores and transformations.
• Ensure data quality, consistency and governance.
• Deliverables: ML‑ready datasets, feature pipelines, validation outputs.

*Deployment, MLOps & Monitoring*

• Deploy and operate models at scale (endpoints, pipelines, CI/CD) and implement monitoring, observability and cost optimization.
• Deliverables: production endpoints, automated pipelines, monitoring/alerting configurations.
• ***Cross‑Functional Collaboration***
• Work with Data Engineers, Platform teams and Business stakeholders to translate use cases into scalable solutions; coordinate with external vendors where needed.
• Deliverables: aligned implementation plans, stakeholder sign‑offs, integration artifacts.

*Continuous Improvement & Enablement*

• Stay current with GCP AI/ML services; optimize models, pipelines and infrastructure; contribute to standards, accelerators and knowledge sharing.
• Deliverables: improved performance/efficiency, best‑practice guides, internal demos and docs.
• Main contacts Business stakeholders, Data Engineering teams, Platform teams, external AI/cloud and technical vendors.

Requirements

• 5+ years in AI/ML engineering.
• Minimum 3+ years recent, hands‑on GCP experience (mandatory).
• Strong hands‑on experience with Vertex AI (training, endpoints, pipelines, experiments) and BigQuery.
• Proficiency in Python and ML/DL frameworks (TensorFlow, PyTorch, scikit‑learn).
• Solid data engineering understanding for ML workloads and ability to translate business problems into AI solutions.
• Bachelor’s degree in Computer Science/AI/Data Science or related field.
• GCP certifications (e.g., Professional Machine Learning Engineer) are a strong plus.