D
Divergent Technologies
AI Solutions Engineer
Skills
DockerTypescriptPythonPyTorchMachine LearningAIKubernetesCompliance
19 days ago
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Important information
Contract type:
Permanent
Salary:
$122,430 – $168,340 / year
Location:
Torrance, CA, USA
Work mode:
Onsite
Published on:
8 October 2026
What they need
- Divergent is a technology company that has architected, invented, built, and commercialized an end-to-end factory system called the Divergent Adaptive Production System (DAPS) that comprehensively uses machine learning to optimally engineer, additively manufacture, and flexibly assemble complex integrated vehicle structures and subsystems
- Products created using DAPS are superior in performance, lower in cost, rapidly customizable to meet mission and customer-specific requirements, faster to market, and scalable on demand to high volume production
- Divergent is a qualified Tier 1 supplier to global automotive OEMs, and Divergent is now expanding to support mission critical needs in the Aerospace and Defense sector
- Join us to be a part of this transformative journey, where your impact will shape the future of technology and production
- We are looking for an AI Solutions Engineer who not only builds cutting‑edge generative‑AI systems but also serves as the AI Enablement lead for the organization
- You’ll design, develop, and productionize large‑language and multimodal model solutions while dedicating a significant portion of your time to help teams adopt AI responsibly and effectively
- Help Build & Deploy AI Solutions
- Collaborate with cross-functional teams to integrate and optimize generative AI solutions into products and processes
- Develop domain specific AI software using RAG and Agentic AI
- Collaborate with the data engineers, product teams, people operations, and legal to ensure compliant and responsible AI
- Implement usage monitoring and bias mitigation to improve result quality
- AI Adoption & Enablement
- Act as the primary internal AI champion, providing guidance, training, and best‑practice workshops for the company
- Create and maintain self‑service resources (playbooks, tutorials, templates) that empower users to build and evaluate AI solutions safely
- Host regular “AI office hours,” one‑on‑one coaching sessions, and webinars to raise AI expertise across the company
- Partner with compliance and ethics teams to embed responsible‑AI checks into everyday workflows
- Gather user feedback, translate it into product requirements, and drive iterative improvements to AI tools and platforms- B.S. in Computer Science/AI/ML (or related) with 3+ years AI/ML engineering experience
- Experience with ML/LLM libraries such as vLLM, LangChain, PyTorch, and HuggingFace
- Understanding of LLMs and multimodal models with their performance considerations and use cases
- Knowledge about prompt engineering, RAG, and building AI Agents
- Ability to create self‑service enablement assets (playbooks, tutorials, reusable component libraries)
- Ability to translate complex technical concepts for non‑technical audiences and collaborate cross‑functionally
- Ability to lawfully access information and technology that is subject to US export controls
- Experience running trainings to teach and promote AI best practices
- Proficient in programming languages such as Python
- Practical experience developing, deploying, and scaling AI Agents in a production environment
- Proven track record of gathering user feedback and iterating on AI tools to improve adoption
- M.S. in Computer Science, AI, ML, or related field
- Proficiency in TypeScript
- Knowledge of ethical AI, compliance frameworks, and safety standards
- Experience with multimodal pipelines and traditional AI/ML methods
- Hands‑on MLOps: CI/CD, Docker, Kubernetes
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