Applied AI Engineer

Job Description

Responsible for serving as a senior technical leader driving the design, development, and deployment of advanced AI solutions that address complex business challenges. Provides deep expertise across domains such as computer vision, natural language processing, recommendation systems, and predictive analytics, while setting strategic direction, establishing best practices, and influencing cross-functional teams to maximize the impact of AI initiatives. The role is onsite, 5 days/week in Irvine, CA.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to View email address on click.appcast.io learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

• Minimum five (5) + years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python.

• Two (2) + years’ experience in Python, PyTorch, TensorFlow, or other machine learning frameworks.

• Must have advance knowledge and experience with C#.

• Proven experience applying large language models (LLMs), generative AI, or OSS agent-based frameworks to business solutions.

• Demonstrated success delivering at least one large-scale ML/AI application or service on a cloud platform (Azure, AWS, or GCP).

• Strong understanding of ML algorithms, deep learning architectures, data structures, and applied optimization techniques.

• Familiarity with MLOps practices and tools (Docker, Kubernetes, MLflow, etc.) for scalable AI/ML deployments.

Ability to translate research and experimental AI approaches into practical, enterprise-grade solutions.