Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowFirst seen 3 days ago

Remote | ML Engineer — $100–$150/hour

24-MAG343 open roles

Pay
$100 – $150 an hour
Where
New York, United States, Remote
Work mode
Remote
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowRemote | ML Engineer — $100–$150/hour24-MAG · New York, United States, Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on 24-MAG's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market. 24-MAG postings stay open a median of 1 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

24-MAG median: 1 days open

The posting

We are sharing a specialised part-time consulting opportunity for experienced Machine Learning Engineers and researchers to contribute to an advanced AI training project focused on model development, training and inference systems, numerical computing, performance optimisation, and Python-based ML engineering.

Selected professionals will create, solve, review, and validate technically demanding machine-learning engineering tasks. The work may involve implementing or modifying models, building reproducible training or inference workflows, optimising system performance, debugging numerical or infrastructure-level failures, and verifying that solutions meet objective correctness and performance requirements.

Key Responsibilities

Machine Learning Development & Validation

  • Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure
  • Implement model components, data pipelines, evaluation systems, and numerical methods
  • Build reproducible technical workflows using Python and command-line tools
  • Work with tensor operations, automatic differentiation, model architectures, tokenisation, batching, and generation
  • Verify that implementations satisfy objective functional, numerical, and performance requirements

Training, Inference & Performance Optimisation

  • Optimise training and inference workflows for latency, throughput, memory utilisation, and hardware efficiency
  • Diagnose numerical instability, incorrect tensor behaviour, memory bottlenecks, and performance regressions
  • Analyse system-level failures across model execution and supporting infrastructure
  • Compare alternative implementations and determine whether results are correct, reproducible, and efficient
  • Evaluate trade-offs involving compute, memory, numerical precision, and model performance

Technical Review & AI-Generated Code Evaluation

  • Review AI-generated code, implementations, and technical solutions for correctness and engineering quality
  • Identify implementation errors, inefficient approaches, weak assumptions, and reproducibility issues
  • Assess whether generated solutions appropriately address the technical requirements of each task
  • Design objective tests, benchmarks, and verification criteria
  • Provide clear written explanations of technical decisions, limitations, and recommended improvements

ML Systems & Engineering Workflows

  • Work with modern machine-learning frameworks, numerical libraries, and inference tooling
  • Apply practical understanding of model training, evaluation, numerical computation, and inference systems
  • Debug ML systems beyond surface-level API usage
  • Document implementation decisions, performance trade-offs, and technical failure modes
  • Maintain rigorous and reproducible engineering practices across assigned tasks

Ideal Profile

  • Master's degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline
  • Strong professional or research experience in machine learning
  • Practical proficiency with Python
  • Meaningful experience with at least two relevant machine-learning frameworks, numerical libraries, or inference tools
  • Strong understanding of model training, evaluation, numerical computation, or inference systems
  • Ability to debug ML systems beyond high-level API usage
  • Ability to explain implementation decisions, performance trade-offs, and failure modes clearly
  • Experience building reproducible technical and programmatic workflows
  • Relevant tools may include PyTorch, JAX, NumPy, SciPy, SGLang, vLLM, llama.cpp, Hugging Face Transformers, Hugging Face Tokenizers, or comparable technologies
  • Experience within an established technology company, AI laboratory, research organisation, or recognised engineering environment is strongly preferred
  • Exceptional open-source or academic experience may also qualify

Engagement Details

  • Part-time independent contractor engagement
  • Fully remote and open globally
  • Approximately 15 hours per week
  • Flexible schedule, including the ability to choose working days and hours
  • Compensation: $100–$150/hour
  • Compensation is output-based, with payment made for tasks that meet project specifications
  • Task completion time may vary depending on technical complexity, experience, and workflow
  • Minimum submission requirements apply
  • Selected professionals should be prepared to begin their first task within approximately 24–48 hours of completing onboarding
  • The selection process may include screening questions, an approximately 30-minute AI interview, a technical assessment where required, and hiring-manager review
  • Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against 24-MAG's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on 24-MAG's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    24-MAG's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.