10850 – Sr. Software Engineer, AI & ML Ops

Hyundai Autoever America•Fountain Valley, CA

About The Position

Hyundai AutoEver America seeks a seasoned Senior AI/ML Engineer to architect, develop, and deploy advanced AI solutions, including LLMs, RAG systems, and intelligent agents—to transform automotive industry applications. This role drives end‑to‑end AI innovation across cloud environments, leads technical strategy, mentors engineers, and collaborates cross‑functionally to deliver scalable, secure, and user‑centric AI systems.

Requirements

Bachelor’s or Master’s degree in Computer Science, Engineering, AI, or related field; advanced degrees/certifications are a plus.
8+ years of software engineering experience, including 3+ years in AI/ML solution development.
Proven experience designing and deploying LLM-based solutions, traditional ML models, RAG systems, and agent workflows.
Strong expertise in Python, TensorFlow/PyTorch, Hugging Face, prompt engineering, vector databases, and AI orchestration.
Hands-on experience with AWS SageMaker/Bedrock, Azure OpenAI, or Azure ML Studio, plus MLOps best practices (CI/CD, testing, model monitoring).
Proficiency in frontend frameworks (React), cloud-native deployment (Docker/Kubernetes), microservice APIs, and relational/NoSQL databases.

Nice To Haves

Experience in the automotive or mobility domain, including telematics, diagnostics, or intelligent vehicle systems.
Background implementing GenAI across poly‑cloud or hybrid environments (Azure, AWS, GCP).
Experience with LLM fine‑tuning, multimodal AI, or autonomous agent frameworks.
Familiarity with LangChain, MLflow, Vertex AI, Dialogflow, Azure Monitor, or similar AI lifecycle tools.
Awareness of ethical/responsible AI, AI security, and emerging GenAI trends.

Responsibilities

Architect and develop scalable AI/ML and LLM-based systems, including RAG pipelines, agentic workflows, predictive models, and generative AI solutions.
Build full‑stack AI applications, including React-based dashboards and front‑end interfaces integrated with backend services and cloud infrastructure.
Develop data pipelines and ML Ops workflows using Python, SQL, AWS/Azure platforms, and monitoring tools to train, deploy, and optimize models.
Lead cross-functional AI initiatives, deliver PoCs/MVPs, ensure compliance with AI governance, and integrate AI features into enterprise and user-facing systems.
Provide technical leadership and mentorship, guiding standards, code reviews, model documentation, and best practices in AI/ML development.
Continuously improve AI performance and reliability through prompt engineering, architecture enhancements, and data optimization.