Machine Learning Engineer

Mercor; Remote; EUR 100.000 - 125.000; Teilzeit

Zusammenfassung

A leading AI talent connector is seeking a Machine Learning Engineer to design scalable ML pipelines and build advanced deep learning models. This remote role requires strong expertise in machine learning and proficiency in Python, with familiarity in frameworks like PyTorch or TensorFlow. The ideal candidate will work closely with data scientists, focusing on data quality and implementing reinforcement learning loops. Compensation is set at $14/hour with flexible working hours between 20 to 40 hours per week.

Qualifikationen

• 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 like Weights & Biases, MLflow, Docker, Kubernetes, or Airflow.
• Experience designing custom architectures or adapting LLMs, diffusion models, or transformer-based systems.

Aufgaben

• 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.

Kenntnisse

Machine learning

Deep learning

Reinforcement learning

Python

MLOps tools

Distributed training

Tools

PyTorch

TensorFlow

JAX

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: [e-mail]

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