Software Engineer, AI

Divergent•Torrance, CA

2d•Onsite

About The Position

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. Purpose We are seeking an AI Software Engineer with a strong background and hands-on experience using the latest technologies in Generative AI along with traditional AI knowledge. You will be working on designing, developing, and deploying AI software leveraging large language models (LLMs) and multimodal models. You will be participating in an end-to-end solution handling including data ingestion, model training, agentic orchestration , inference optimization, and production deployment. This role will be key to building autonomous AI Agents that improve process efficiency and product quality at Divergent.

Requirements

Ability to lawfully access information and technology that is subject to US export controls
Proficient in programming languages such as Python and C++.
Familiarity with data structures and algorithms.
Understanding of LLMs and multimodal models with their performance considerations and use cases.
Deep expertise in agentic design patterns, including tool-use (function calling), iterative reasoning loops, and autonomous error correction.
Experience using agent-centric frameworks such as LangGraph, or advanced implementations of LangChain and LlamaIndex.
Experience with ML/LLM libraries such as vLLM, PyTorch, and HuggingFace.
Practical experience developing, deploying, and scaling production-grade AI Agents and multi-agent systems.
Bachelor's in Computer Science, AI, ML or related field.
3+ years of experience in AI/ML engineering.
Excellent communication and collaboration skills

Nice To Haves

Master’s or Ph.D. in Computer Science, AI, ML or related field.
Knowledge about ethical AI, compliance frameworks, and safety in AI.
Experience developing multimodal pipelines.
Hands-on experience with traditional AI, ML, and Deep learning methods and libraries.
Proficient in programming languages such as C#, TypeScript.
Knowledge of MLOps, CI/CD pipelines, and containerization (Docker, Kubernetes).
Strong publication record in the field of AI.

Responsibilities

Design, develop, and deploy innovative generative AI models and algorithms using the latest deep learning techniques.
Collaborate with cross-functional teams to integrate and optimize generative AI solutions into products and processes.
Select and fine-tune the state-of-the-art generative process for the given use case.
Architect domain-specific AI software using agentic workflows, multi-agent orchestration, and advanced state management.
Determine hardware requirements and optimize inference performance for generative AI pipelines.
Collaborate with the infrastructure team to design the deployment architecture.
Collaborate with the data engineers, product teams, people operations, and legal to ensure compliant and responsible AI.
Implement model monitoring, agent reliability tracking, and bias mitigation to improve result quality.