Machine Learning Engineer
$160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

3 weeks remote, 7 weeks onsite in Austin, TX
80–100 hours/week for 10 weeks
In-person
Short-term contract
full-time (90 hrs/week)

Machine Learning Engineer   $160K–$200K+ Offers For Graduates $160K–$200K+ Offers For Graduates 

Description

Engineers frequently discuss creating meaningful work. This opportunity requires you to deliver: continuous delivery under evaluation, rigorous assessment protocols, and operational AI infrastructure directly influencing United States government functions. No credential posturing. No abstract assignments. Only production deliverables each week, executed under demanding conditions.

Gauntlet for America is a fully funded, competitive 10-week fellowship built to develop AI-native engineering capacity for the United States government. It functions as a high-pressure validation environment for seasoned engineers seeking to prove their capability to construct and maintain production-quality AI systems in contexts where dependability, security, and tangible impact are paramount.

Participants deliver weekly outputs, function under rigorous evaluation, and develop skills alongside other exceptional engineers. After successful program completion, graduates transition into federal GS-12 engineering positions (~$150K + comprehensive federal benefits), contributing to systems that directly affect government operations.

The program spans 10 weeks: 3 weeks conducted remotely, then 7 weeks onsite in Austin, Texas. Participants should anticipate a demanding schedule (80–100 hours/week) engineered to accelerate learning velocity, signal generation, and career progression.

Outcomes:

  • 10+ production-ready AI systems delivered throughout the fellowship
  • Direct placement into a federal engineering role (GS-12 equivalent, ~$160K–$200K+ depending on experience + full benefits)
  • Contribute to high-impact systems defining how the U.S. government constructs and operates technology
  • Enter a network of AI-native engineers operating at the frontier of public sector innovation

If you are prepared to be assessed on what you deliver — not your educational background — apply now.

What you will be doing

  • Deliver production-ready AI applications weekly against firm deadlines
  • Develop using modern AI-first methodologies (agents, tool use, evals, retrieval, deployment)
  • Collaborate and compete with elite engineering talent in a high-feedback setting
  • Engage with authentic, ambiguous problem domains resembling government and enterprise contexts
  • Convert actual briefs into scoped, dependable, deployable systems

What you will NOT be doing

  • Participating in theoretical coursework or passive instruction — every hour centers on building and shipping
  • Waiting months for production deployment — you'll release functional systems each week
  • Depending on credentials, pedigree, or interview performance for placement — your production output is the sole evaluation criterion
  • Operating in a low-stakes environment — the systems you construct function under authentic security and reliability requirements

Key responsibilities

Deliver production-grade AI systems under real-world constraints that demonstrate readiness for federal engineering roles.

Candidate requirements

  • U.S. citizenship required (no exceptions; background check required)
  • Demonstrated engineering ability (new grads and experienced engineers considered)
  • Willing to relocate to Austin, TX for 7 weeks (full-time, in person)
  • Willing to relocate to the Washington, DC area upon program completion (no remote roles)
  • Strong problem-solving ability, learning speed, and clear reasoning under pressure
  • High responsiveness to feedback and ability to operate in high-intensity environments

Meet a successful candidate

Watch Interview
Fabiano Lucchese
Fabiano  |  SVP of Software Engineering
Brazil

Does your company encourage your natural creativity? This Brazilian engineering leader rediscovered his purpose after unleashing both his an...

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Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.

Chat-style
screening interview.
STEP 1

Chat-style
screening interview.

Cognitive 
aptitude test.
STEP 2

Cognitive 
aptitude test.

Prove real-world 
job skills.
STEP 3

Prove real-world 
job skills.

Interview with the hiring manager.
STEP 4

Interview with the hiring manager.

Pass
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STEP 5

Pass
proctored test.

Accept job offer.
STEP 6

Accept job offer.

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What you will learn

Phase 1: Remote (Weeks 1–3) — AI-First Engineering Foundations

  • AI-first development workflows (coding agents, MCP, real-time collaboration)
  • Retrieval-Augmented Generation (RAG), embeddings, and vector databases
  • Rapid project sprints focused on shipping under constraints

Phase 2: Onsite in Austin (Weeks 4–10) — Production AI at Scale

  • Agent systems, evals, verification, and observability (LangChain/LangSmith/LangFuse/CrewAI)
  • Enterprise-grade delivery: QA, reliability, and high-standards execution
  • Fine-tuning + deployment patterns (LoRA/QLoRA + production integration)
  • Multi-agent modernization of real-world codebases
  • Multimodal AI builds (image/video/voice) and scalable infrastructure (AWS/Azure)

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Premium pay for premium talent

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