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Artificial Intelligence Engineer Trainee Jobs in California

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Artificial Intelligence Engineer Trainee information

What does an artificial intelligence engineer trainee do?

An Artificial Intelligence Engineer Trainee learns and assists with designing, developing, and deploying AI models and systems under the supervision of experienced engineers. Their responsibilities often include data preprocessing, building and testing machine learning algorithms, and supporting the integration of AI solutions into existing products or services. Trainees may also work on tasks related to natural language processing, computer vision, or predictive analytics, and are expected to keep up-to-date with the latest AI research and technologies. This role is ideal for individuals who are starting their careers in AI and want hands-on experience while enhancing their technical and problem-solving skills.

What are the key skills and qualifications needed to thrive as an artificial intelligence engineer trainee?

To thrive as an Artificial Intelligence Engineer Trainee, a solid background in computer science, mathematics, and programming languages like Python is essential, often supported by a relevant degree or coursework. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and version control systems is typically expected. Strong analytical thinking, problem-solving ability, and willingness to learn new technologies help trainees stand out in this evolving field. These skills and qualities are crucial for effectively developing, testing, and deploying AI models in real-world applications.

What are some common challenges faced by artificial intelligence engineer trainees during their first projects?

As an Artificial Intelligence Engineer Trainee, you may encounter challenges such as understanding complex datasets, managing data preprocessing, and bridging the gap between theoretical knowledge and real-world applications. Collaborating with cross-functional teams, learning to select appropriate machine learning models, and debugging code are also common hurdles. However, these challenges offer valuable learning opportunities and are typically addressed with mentorship, hands-on practice, and access to collaborative team resources.
What are the most commonly searched types of Artificial Intelligence Engineer jobs in California? The most popular types of Artificial Intelligence Engineer jobs in California are:
What job categories do people searching Artificial Intelligence Engineer Trainee jobs in California look for? The top searched job categories for Artificial Intelligence Engineer Trainee jobs in California are:
What cities in California are hiring for Artificial Intelligence Engineer Trainee jobs? Cities in California with the most Artificial Intelligence Engineer Trainee job openings:
Infographic showing various Artificial Intelligence Engineer Trainee job openings in California as of August 2026, with employment types broken down into 81% Full Time, 13% Part Time, 2% Temporary, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.

Sr. Director, Enterprise Artificial Intelligence

Staar Surgical

Lake Forest, CA • On-site

Full-time

Posted 5 days ago


Job description

MAIN JOB RESPONSIBILITIES / COMPETENCIES
The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.
This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.
1. Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
2. Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
3. Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
4. Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
5. Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
6. Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
7. Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
8. Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
9. Establish KPIs and executive dashboards measuring AI adoption and business value.
10. Lead organizational change management and enterprise AI adoption.
11. Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
12. Evaluate emerging AI technologies and strategic technology partnerships.
13. Foster innovation, continuous improvement, and responsible AI adoption.
14. Other duties as assigned.
REQUIREMENTS
EDUCATION & TRAINING
• Bachelor's degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
• Advanced degree preferred.
• Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.
EXPERIENCE
• 12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
• 3+ years leading enterprise digital AI transformation organizations.
• Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
• Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
• Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
• Experience presenting AI strategies and business outcomes to executive leadership and Boards.
• Enterprise AI governance, organizational change management, and global business transformation.
• FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.
SKILLS
• Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
• Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
• Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
• Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
• Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
• Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
• Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
• Ability to partner effectively with Executive Leadership, Information Technology, Manufacturing, Engineering, Supply Chain, Quality Assurance, Regulatory Affairs, Finance, Human Resources, Cybersecurity, Legal, and external technology partners to deliver enterprise-wide AI capabilities.
• Excellent analytical, strategic planning, organizational, communication, executive presentation, negotiation, financial management, vendor management, stakeholder engagement, and organizational change management skills.
• Demonstrated leadership building, mentoring, and scaling high-performing multidisciplinary teams consisting of AI Engineers, Data Scientists, Machine Learning Engineers, AI Solution Architects, Enterprise Architects, Product Managers, and business technology professionals.
• Proven ability to lead enterprise modernization initiatives, drive innovation, establish AI governance, manage organizational change, and deliver measurable business transformation while maintaining secure, scalable, and responsible AI practices.
Pay range: $200K - $300K - Final compensation/salary will depend on experience.
STAAR Surgical is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law. #USA