Machine Learning Engineer
$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  

Description

Gauntlet is a selective, fully funded 10-week fellowship designed for experienced engineers seeking to advance their careers by demonstrating their ability to build and deploy production-quality AI systems under real-world constraints. Participants ship deliverables weekly, collaborate with seasoned operators, and gain direct access to founders, CTOs, and hiring partners.

Fellows in our latest cohort earned 300+ first-round interviews with hiring partners. We aim for 100% of graduates to receive offers from our partner network, with starting compensation no lower than $200,000.

The fellowship spans 10 weeks: the first 3 weeks are conducted remotely, followed by 7 weeks onsite in Austin, Texas. Participants should anticipate a demanding schedule (80–100 hours per week) structured to optimize learning velocity, performance visibility, and career advancement.

Outcomes:

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

If you ship quickly, thrive under pressure, and prefer that your work — rather than your resume — defines your next opportunity, apply now.

What you will be doing

  • Deliver production-quality AI applications weekly under firm deadlines
  • Work with contemporary AI-first development practices (agents, tool integration, evaluations, retrieval, deployment)
  • Engage and compete with leading engineering talent in a high-feedback setting
  • Showcase your work directly to CTOs, founders, and hiring partners
  • Convert real project briefs into scoped, dependable, deployable solutions

What you will NOT be doing

  • Spending multiple weeks on theory, tutorials, or passive study without deploying
  • Creating demos that never encounter real users or evaluation
  • Refining resumes and portfolios rather than constructing and shipping functional systems
  • Attending weeks of lectures and coursework before engaging with actual code

Key responsibilities

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

Candidate requirements

  • 3+ years of professional engineering experience (or equivalent capability)
  • 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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