Applied AI Engineer

Idelsoft; San Francisco (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Unlimited PTO

Full health insurance

Free lunch and dinner

Company equipment provided

Job summary

Idelsoft seeks an Applied AI Engineer to own mission-critical agent systems end-to-end in a stealth, seed-stage AI company serving regulated domains. You will design and optimize workflows, reason over structured data, and fine-tune models for production use, working closely with customers and the broader team.

You will move ideas to production rapidly, shaping architecture choices and product direction while ensuring reliability and compliance in real-world deployments.

Qualifications

• Bachelor’s or higher in Computer Science, ML, or equivalent practical experience
• Strong familiarity with LLM architectures and current agent research
• Excellent programming skills with ML libraries — PyTorch, Hugging Face, W&B
• Experience building production ML or AI systems, not just research prototypes
• Solid practical experience with search and information retrieval
• Moves fast from idea to production, with genuine care for customer experience
• Based in or willing to relocate to San Francisco (or exceptional enough to justify remote)

Responsibilities

• Own agent workflows and infrastructure for domain-specific engineering agents
• Reason over complex design data and integrate with engineering tools
• Post-training and fine-tuning models for domain-specific needs
• Collaborate directly with customers to deliver reliable production workflows
• Prototype, validate with real users, and ship frequently
• Influence engineering culture, architecture decisions, and product direction

Skills

LLM architectures

Agent workflows

Production ML systems

Search & IR

Python

PyTorch

Hugging Face

Weights & Biases

Education

Bachelor's degree in Computer Science / ML

Tools

PyTorch

Hugging Face

Weights & Biases (W&B)

Job description

About the job Applied AI Engineer

We’re recruiting on behalf of a stealth, seed-stage AI company building agent systems for a highly regulated, physical-world engineering domain. Their customers are large global enterprises with real safety constraints, real compliance requirements, and decades of accumulated technical data that no one has been able to make an AI reason over reliably. That’s the problem you’d be hired to solve.

The company is backed by two of the most recognized firms in venture, plus a strategic investor from the industry they serve. The founding team is unusual: AI researchers from a top university lab, a global legal and compliance leader from a major technology company, senior operating executives from large industrial manufacturers, and a former head of a US federal regulatory agency. It’s a genuine mix of AI, deep engineering, and policy — which is exactly what the problem requires.

You’d be among the first technical hires, owning mission-critical systems end to end.

What You’ll Own

• Agent workflows and infrastructure. Core systems for domain-specific engineering agents — intelligent context management, novel indexing approaches, and advanced data structures.
• Reasoning over complex design data. Agents and models that interpret, reason over, and manipulate highly structured technical data, integrated with enterprise-grade engineering tools.
• Post-training. Customizing and fine-tuning models for a domain where generic performance isn’t good enough.
• Direct customer collaboration. Working alongside customers to deliver workflows that are reliable, intuitive, and trusted in production — not demos.
• Speed. Prototype, validate with real users, ship frequently.
• Company shape. Influence on engineering culture, architecture decisions, and product direction.

What We’re Looking For

Must-have

• Bachelor’s or higher in Computer Science, Machine Learning, or equivalent practical experience
• Strong familiarity with LLM architectures and current agent research
• Excellent programming skills with ML libraries — PyTorch, Hugging Face, W&B
• Experience building production ML or AI systems, not just research prototypes
• Solid practical experience with search and information retrieval
• Moves fast from idea to production, with genuine care for customer experience
• Based in or willing to relocate to San Francisco (or exceptional enough to justify remote)

Nice-to-have

• 2 years in applied ML, backend engineering, or AI infrastructure
• Experience with machine learning over geometric or highly structured technical data
• Post-training or fine-tuning experience
• Background in a domain with real physical or regulatory constraints
• Prior founding experience
• High-impact contributions or published work at a top-tier AI lab or team

Culture

The team is intentional with its time — hard work on meaningful problems, and protected personal time. Success is defined by customer outcomes and by the team’s own professional growth. Expect ambiguity, real constraints, and high expectations.

Benefits

• Unlimited PTO
• Full health insurance
• Free lunch and dinner
• Company equipment provided