Create end-to-end AI system blueprints, encompassing data ingestion, processing, model training, and deployment.
Evaluate and choose AI frameworks, platforms, and tools that meet business requirements, partnering with key technology and business stakeholders.
Oversee the transition from POC (Proof of Concept) to production, ensuring continuous model monitoring, retraining, and stability.
Define strategies for collecting, cleaning, and managing high-quality datasets for training.
Embed AI ethics, data privacy, and security controls within the architecture.
Translate complex AI concepts into actionable business strategies for non-technical stakeholders.

Requirements

Deep knowledge of AI/ML algorithms, neural networks, Natural Language Processing (NLP), and data engineering.
Previous experience as an AI Engineer, Data Scientist, or technical leader is highly valued.
Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
Proficiency in Python and familiarity with data manipulation tools.
Ideally a degree in Computer Science, Data Science, or AI.
Strong leadership, communication, and strategic thinking capabilities.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI algorithmsML algorithmsneural networksNatural Language Processingdata engineeringPythondata manipulation

Soft Skills

leadershipcommunicationstrategic thinking