Software Engineer - Edge AI Systems

Los Angeles +5 · Hybrid$145k – $275k + EquityNo Visa Sponsorship

About this role

The Role

We are seeking an experienced Software Engineer to join a newly-formed team focused on developing and deploying advanced AI systems to the tactical edge. This role involves training, evaluating, and deploying LLM agents to edge hardware for interfacing with sensors, effectors, and drone systems. This project is in support of multiple customers in the defense sector that are looking for untethered AI solutions that can be rapidly deployed downrange on hardware with limited capabilities. As a part of this team, you will build and deploy specialized models and agents that can run on tactical edge hardware, working alongside other experts in AI, LLMs, and systems to shape solutions that redefine complex tactical defense scenarios.

Core Responsibilities

Train and fine-tune edge-capable LLMs for tactical defense applications

Optimize model performance for various edge hardware (GPU, CPU, and specialized accelerator) platforms

Design and implement multi-agent systems for various mission scenarios

Interface LLM agents with sensors, effectors, and drone systems

Benchmark and evaluate agent capabilities, performance, and reliability

Engineer scalable, reliable, and fail-safe systems capable of functioning in high-stakes environments

What We Value

Proven experience in AI model development, training, and fine-tuning

Experience building LLM agent systems using direct LLM API calls, or frameworks such as LangChain

Experience optimizing AI models and runtime performance for edge hardware

Familiarity with edge AI optimization tools including Ollama, Mojo, TVM, TF Lite, and vLLM

Experience working in the defense sector, especially with weapon and UxV systems, is highly desirable

Ability to manage complexity, optimize for performance, and think critically under pressure

Experience deploying and maintaining robust production systems

What We Require

5+ years of professional software development experience

2+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and existing systems

Experience building and deploying LLMs and LLM agents using modern frameworks such as PyTorch, HuggingFace Transformers, LangChain, and vLLM

Strong proficiency in Rust, Python, or C++

Bachelor's/Master's/PhD in Computer Science, Physics, Mathematics, or related fields

Active US Security clearance or eligibility and willingness to obtain a US Security clearance

Company at a glance

Palantir is a publicly traded software company specializing in data integration and analysis solutions for government agencies and enterprises across national security, healthcare, energy, finance, and manufacturing sectors.

Founded2003
Team Size5001-10000
WorkspaceHybrid
StageSeries E+
IndustryData Infrastructure and Analytics
Locations
Los Angeles, CA, United States ·New York, NY, USA ·Palo Alto, CA, USA ·San Francisco, CA, United States ·Seattle, WA, USA ·Washington, DC, USA
Investors
Founders Fund ·Glynn Capital ·Ulu Ventures
LinkedInLinkedIn

What happens next

Skip the application pile. I get you in front of the people who decide.

Confirm the fit

A few questions to make sure this role is the right shape for you. Two minutes.

I pitch you to the company

I write the intro, send it to the founder, and handle the back-and-forth.

A meeting lands on your calendar

When the company wants to meet, I get the call on your calendar. You just show up.

Culture & values

Celebrate individuals' strengths, skills, and interests from first interview to long-term growth

Do not rely on traditional career ladders

Pay attention to the needs of the community to optimize growth opportunities

Ensure many pathways to success at Palantir

Believe employees are 'better together'

In-person work affords opportunity for more creative outcomes

Encourage employees to work from offices to foster connectivity and innovation

Many teams offer hybrid options allowing employees to work from home one or two days a week

Allow employees to strike the right trade-off for their personal productivity

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