Associate AI Specialist

Rand Technology LLC•Irvine, CA

1d•Hybrid

About The Position

POSITION SUMMARY The Associate AI Specialist supports the development, implementation, and optimization of artificial intelligence and machine learning solutions to enhance business operations, improve decision-making, and drive innovation. This role works collaboratively with cross-functional teams to identify AI opportunities, develop proof-of-concepts, and deploy AI-powered tools and applications that align with company objectives.

Requirements

Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, Statistics, or related field
Master's degree preferred or equivalent practical experience
1-3 years of experience in AI, machine learning, data science, or related field
Hands-on experience developing and deploying AI/ML models
Experience with AI/ML projects in a business or academic setting
Portfolio or examples of AI projects demonstrating practical application
Internship or co-op experience in AI/ML considered
Proficiency in Python and/or R for AI/ML development
Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn, Keras)
Knowledge of AI/ML algorithms and techniques (supervised/unsupervised learning, neural networks, NLP)
Familiarity with cloud AI platforms (Azure AI, AWS SageMaker, Google Cloud AI)
Understanding of data manipulation libraries (Pandas, NumPy)
Experience with SQL and database systems
Knowledge of version control systems (Git)
Familiarity with data visualization tools (Tableau, Power BI, Matplotlib)
Strong analytical and problem-solving skills
Excellent attention to detail and commitment to quality
Effective communication skills with technical and non-technical audiences
Ability to work independently and collaboratively
Quick learner with curiosity and passion for emerging technologies
Project management and organizational skills
Creative thinking and innovation mindset
Adaptability in fast-paced, evolving environment

Nice To Haves

Experience with generative AI technologies (GPT, LLMs, prompt engineering)
Knowledge of computer vision and image processing
Experience with AI model deployment and MLOps practices
Familiarity with Agile/Scrum methodologies
Understanding of AI ethics, bias, and responsible AI principles
Experience in technology, telecommunications, or distribution industry
Certifications in AI/ML (Microsoft AI, AWS ML, Google ML, etc.)
Experience with business intelligence and analytics platforms
Knowledge of robotic process automation (RPA) tools
Contributions to open-source AI projects or publications

Responsibilities

Assist in designing, developing, and implementing AI and machine learning models
Support the creation of proof-of-concepts and pilot projects for AI initiatives
Develop and maintain AI-powered applications and tools for business use cases
Optimize existing AI models for performance, accuracy, and efficiency
Document technical specifications, methodologies, and implementation processes
Collect, clean, and prepare datasets for AI model training and testing
Conduct exploratory data analysis to identify patterns and insights
Ensure data quality, integrity, and compliance with privacy regulations
Create and maintain data pipelines for AI applications
Work with databases, APIs, and data integration tools
Integrate AI solutions with existing business systems and workflows
Support deployment of AI models to production environments
Monitor AI system performance and implement improvements
Troubleshoot and resolve technical issues with AI applications
Collaborate with IT teams on infrastructure and security requirements
Partner with business stakeholders to understand requirements and pain points
Identify opportunities where AI can add value to business processes
Translate business needs into technical AI solutions
Present findings, recommendations, and project updates to leadership
Provide training and support to end-users on AI tools and applications
Stay current on AI/ML trends, technologies, and best practices
Research and evaluate emerging AI tools, platforms, and frameworks
Experiment with new AI techniques and methodologies
Contribute to the development of AI strategy and roadmap
Share knowledge and insights with team members
Develop intelligent automation solutions using AI technologies
Implement natural language processing (NLP) applications
Create chatbots, virtual assistants, or conversational AI tools
Automate repetitive tasks using machine learning and AI
Support process improvement initiatives with AI-driven insights