Support a leading automotive company's AI and ML engineering capability within their TOP platform, focusing on model fine-tuning oversight, agentic orchestration architecture, and LLM evaluation.
Required Skills & Qualifications
2–5 years of experience in technical communication, translating complex technical concepts into clear documentation.
2–5 years of experience in effective communication across cross-functional teams.
2–5 years of hands-on experience with Google Cloud Platform services relevant to AI/ML and data workloads.
2–5 years of experience building and evaluating machine learning models using TensorFlow or TensorFlow Extended.
3–5 years of applied machine learning experience, including feature engineering and model deployment.
5 or more years of professional experience in machine learning engineering, AI systems development, or applied AI research.
Experience fine-tuning LLMs in a cloud environment, preferably Google Cloud Vertex AI.
Strong understanding of MLOps practices.
Strong written and verbal communication skills.
Applicants must be able to work directly for Artech on W2.
Preferred Skills & Qualifications
1–3 years of exposure to telematics data systems.
Experience in automotive diagnostics, vehicle telematics, or connected vehicle platforms.
Google Cloud Professional Machine Learning Engineer certification.
Day-to-Day Responsibilities
Oversee vendor fine-tuning of Google Cloud Vertex AI using proprietary diagnostic data.
Design and build the Orchestration Layer integrating AI engines with platform services.
Evaluate AI engine outputs and drive iterative improvement through structured feedback loops.
Build internal tooling for model monitoring, drift detection, and retraining triggers.
Collaborate with data engineering teams to define data preparation requirements.
Contribute to the long-term insourcing roadmap by documenting model architectures.
Represent AI and ML engineering in architecture reviews and vendor technical discussions.
For immediate consideration please click APPLY to begin the screening process.