About the role

Technical Architect leading AI/ML development in automotive projects with Google Cloud AI. Focusing on intelligent chatbot systems and collaboration with cross-functional teams in hybrid model.

Responsibilities

Architect, design, and lead the development of AI/ML solutions, with a primary focus on intelligent chatbot systems using Google Cloud AI products
Build advanced chatbots that act as intelligent agents, capable of retrieving and delivering information from company-approved data sources
Implement NLP and NLU systems to improve natural conversational experiences and context-aware interactions
Design and deploy scalable, reliable, and secure AI systems into production environments
Collaborate with cross-functional teams, including data scientists, product managers, and software engineers, to deliver AI-driven business solutions
Integrate diverse data sources and APIs to enable accurate, real-time responses within chatbot workflows
Develop personalization and contextual features to enhance user engagement and customer satisfaction
Establish strategies for continuous learning and performance optimization using ML feedback loops
Ensure adherence to data privacy regulations, security standards, and NHTSA/TREAD compliance requirements
Provide technical leadership, guidance, and mentoring to engineering teams
Conduct architecture reviews, provide accurate estimates, and ensure solutions meet business goals and timelines
Stay current with emerging AI/ML research, cloud-native technologies, and conversational AI best practices
Work a hybrid schedule, coming into the Auburn Hills office at least three days per week

8+ years of professional experience in AI/ML architecture and engineering
5+ years of hands-on experience designing, developing, and deploying chatbot solutions in production
Deep expertise with Google Cloud AI products, including Vertex AI, Google Cloud AI Platform, Dialogflow, Cloud Natural Language API, Cloud Translation API, and TensorFlow is required
Strong understanding of NLP, NLU, and ML algorithms for conversational AI
Proficiency in programming languages commonly used in AI/ML development (Java, Python, Go)
Experience architecting scalable, secure AI solutions on cloud platforms (GCP required; AWS or Azure a plus)
Hands-on experience integrating chatbots with enterprise data sources, APIs, and knowledge systems
Familiarity with MLOps tools and practices for managing AI/ML model lifecycles
Experience with speech recognition and text-to-speech technologies
Familiarity with reinforcement learning techniques for chatbot optimization
Prior experience with TREAD reporting is required
Prior experience working with NHTSA standards and regulations is required
Strong knowledge of data privacy, compliance, and security best practices in AI/ML solutions
Proven ability to lead projects, mentor engineers, and align AI solutions with business needs