Software Engineer, AI (Generative AI, LLMs)

TL;DR

Software Engineer, AI (Generative AI, LLMs): Designing, developing, and deploying AI software that leverages large language models (LLMs) and multimodal models with an accent on agentic workflows, multi-agent orchestration, and inference optimization. Focus on building autonomous AI Agents end-to-end—from data ingestion and model training to production deployment, monitoring, reliability tracking, and bias mitigation.

Location: Torrance, California, United States

Pay Range: $122,573 - $168,340 USD

Company

Divergent builds an end-to-end factory system that uses machine learning to engineer, manufacture, and assemble complex integrated vehicle structures and subsystems.

What you will do

• Design, develop, and deploy generative AI models and algorithms using modern deep learning techniques.
• Integrate and optimize generative AI solutions into products and production processes with cross-functional teams.
• Select and fine-tune state-of-the-art generative approaches for specific use cases.
• Architect domain-specific AI software using agentic workflows, multi-agent orchestration, and advanced state management.
• Optimize inference performance by determining hardware requirements for generative AI pipelines.
• Implement model monitoring, agent reliability tracking, and bias mitigation for improved result quality.

Requirements

• 3+ years of experience in AI/ML engineering.
• Hands-on experience with LLMs and multimodal models, including performance considerations and use cases.
• Deep expertise in agentic design patterns, including tool-use (function calling), iterative reasoning loops, and autonomous error correction.
• Experience with agent-centric frameworks such as LangGraph, or advanced implementations of LangChain and LlamaIndex.
• Experience with ML/LLM libraries such as vLLM, PyTorch, and HuggingFace.
• Ability to lawfully access information and technology subject to US export controls.

Nice to have

• Master’s or Ph.D. in Computer Science, AI, ML, or related field.
• Knowledge of ethical AI, compliance frameworks, and AI safety.
• Experience developing multimodal pipelines.
• Proficiency in C# and TypeScript.
• Knowledge of MLOps, CI/CD pipelines, and containerization (Docker, Kubernetes).

Culture & Benefits

• Onsite work environment.
• Holistic compensation package including salary, equity, and discretionary results-based incentive bonus opportunities.
• Paid vacation, sick time, company holidays, and a year-end shutdown; paid parental leave.
• Comprehensive health and wellness benefits (HMO and Premium PPO), plus company-sponsored life insurance and short/long-term disability coverage.
• Learning and development reimbursement to support professional growth.

Hiring process

• Interview process to evaluate technical fit for generative AI, LLMs, and agentic systems.
• Assessment of collaboration and communication skills.