Machine Learning Engineer
$200,000+ Offers For Graduates $200,000+ Offers For Graduates 

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

Machine Learning Engineer   $200,000+ Offers For Graduates $200,000+ Offers For Graduates 

Description

Gauntlet is a selective, fully funded 10-week fellowship designed for experienced engineers committed to proving they can build and deploy production-quality AI systems under real-world conditions. Fellows deliver weekly, collaborate with seasoned operators, and gain direct access to founders, CTOs, and hiring partners.

Challengers in our most recent cohort earned 300+ first-round interviews with hiring partners. We aim for 100% of graduates to secure offers from our partner network, with minimum starting compensation of $200,000.

The fellowship spans 10 weeks: 3 weeks conducted remotely, then 7 weeks onsite in Austin, Texas. Participants should anticipate an intensive schedule (80–100 hours/week) engineered to maximize learning velocity, professional signal, and career advancement.

Outcomes:

  • 10+ production AI applications deployed throughout the fellowship
  • Entry to Gauntlet's alumni and hiring partner network
  • Graduates secure job offers starting at $200,000+ from hiring partners

If you ship quickly, thrive under pressure, and want your work — not your credentials — to define your next opportunity, apply now.

What you will be doing

  • Deliver production-ready AI applications weekly under strict time constraints
  • Work with modern AI-first tooling (agents, tool use, evaluations, retrieval, deployment)
  • Compete and collaborate with elite engineering talent in a high-feedback setting
  • Present completed work directly to CTOs, founders, and hiring partners
  • Convert real briefs into scoped, dependable, deployable systems

What you will NOT be doing

  • Spending weeks on theoretical content, tutorials, or passive learning without delivery
  • Creating demos that are never exposed to real usage or assessment
  • Refining resumes and portfolios instead of constructing and shipping actual systems
  • Enduring weeks of lectures and coursework before engaging with production code

Key responsibilities

Build and deploy production-grade AI systems on a weekly basis, transforming demonstrated engineering performance into $200K+ career outcomes via Gauntlet's hiring partner network.

Candidate requirements

  • 3+ years of professional engineering experience (or equivalent ability)
  • Have independently designed, implemented, and deployed at least one working software system to production or active users
  • High responsiveness to feedback and extreme execution intensity
  • Authorized to work in the U.S. without visa sponsorship
  • Willing to commit to 80–100 hour weeks and relocate to Austin for 7 weeks

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...

Meet Fabiano

Applying for a role? Here’s what to expect.

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
proctored test.
STEP 5

Pass
proctored test.

Accept job offer.
STEP 6

Accept job offer.

Frequently asked questions

About Crossover

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)

Meet some people who've landed similar jobs

Why Crossover

Recruitment sucks. So we’re fixing it.

The Olympics of work

The Olympics of work

It’s super hard to qualify—extreme quality standards ensure every single team member is at the top of their game.

Premium pay for premium talent

Premium pay for premium talent

Over 50% of new hires double or triple their previous pay. Why? Because that’s what the best person in the world is worth.

Shortlist by skills, not bias

Shortlist by skills, not bias

We don’t care where you went to school, what color your hair is, or whether we can pronounce your name. Just prove you’ve got the skills.

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