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Machine Learning Engineer - Remote Role

Mercor

Remote

EUR 60.000 - 80.000

Teilzeit

Heute
Sei unter den ersten Bewerbenden

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Zusammenfassung

A leading AI tech company seeks a Machine Learning Engineer to design scalable ML pipelines, build deep learning models, and collaborate with data scientists. The candidate should have a strong background in machine learning, proficient Python skills, and experience with MLOps tools like Docker and Kubernetes. This is a remote hourly contract position with a commitment of 20-40 hours per week, offering competitive pay.

Qualifikationen

  • Strong background in machine learning, deep learning, or reinforcement learning.
  • Understanding of training infrastructure, including GPUs/TPUs and optimization.
  • Experience designing custom architectures or adapting modern ML models.

Aufgaben

  • Design and implement scalable ML pipelines for training and evaluation.
  • Collaborate with data scientists to collect and preprocess training data.
  • Optimize inference speed and memory efficiency.

Kenntnisse

Machine learning knowledge
Deep learning knowledge
Proficient in Python
Familiar with PyTorch, TensorFlow, or JAX
Experience with MLOps tools

Tools

Docker
Kubernetes
Airflow
Jobbeschreibung
About The Job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Machine Learning Engineer

Type: Hourly contractor

Compensation: $14/hour

Location: Remote

Commitment: 20–40 hours/week

Role Responsibilities
  • Design and implement scalable ML pipelines for model training, evaluation, and continuous improvement.
  • Build and fine-tune deep learning models for reasoning, code generation, and real-world decision-making.
  • Collaborate with data scientists to collect and preprocess training data, ensuring quality and representativeness.
  • Develop benchmarking tools that test models across reasoning, accuracy, and speed dimensions.
  • Implement reinforcement learning loops and self-improvement mechanisms for agent training.
  • Work with systems engineers to optimize inference speed, memory efficiency, and hardware utilization.
Qualifications
Must‑Have
  • Strong background in machine learning, deep learning, or reinforcement learning.
  • Proficient in Python and familiar with frameworks such as PyTorch, TensorFlow, or JAX.
  • Understanding of training infrastructure, including distributed training, GPUs/TPUs, and data pipeline optimization.
  • Experience with MLOps tools (e.g., Weights & Biases, MLflow, Docker, Kubernetes, or Airflow).
  • Experience designing custom architectures or adapting LLMs, diffusion models, or transformer-based systems.
Compensation & Legal
  • Hourly contractor
  • Paid weekly via Stripe Connect
Application Process (Takes 20–30 mins to complete)
  • Upload resume
  • AI interview based on your resume
  • Submit form
Resources & Support
  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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