Remote Machine Learning Engineer - AI Systems Development

About the Role

We are seeking a Remote Machine Learning Engineer to join our dynamic team at Keystone Recruitment. In this role, you will design, train, and deploy large-scale learning systems that power autonomous AI agents. The ideal candidate will thrive in a remote work environment and enjoy the challenge of building models that learn, adapt, and perform complex tasks in real-world settings.

What You'll Do

• Design and implement scalable machine learning pipelines for training, evaluation, and continuous improvement.
• Build and fine-tune deep learning models for reasoning, decision-making, and real-world task execution.
• Collaborate with data scientists to collect, preprocess, and validate high-quality training data.
• Develop benchmarking and evaluation tools to measure accuracy, speed, and reasoning quality.
• Implement reinforcement learning loops and self-improvement mechanisms for agents.
• Optimize inference speed, memory usage, and hardware efficiency in collaboration with systems engineers.
• Maintain experiment tracking, reproducibility, and version control for all models.
• Contribute to research initiatives to improve learning strategies, fine-tuning methods, and model generalization.

Requirements

• Strong background in machine learning, deep learning, or reinforcement learning.
• Proficiency in Python and experience with PyTorch, TensorFlow, or JAX.
• Understanding of distributed training, GPUs/TPUs, and data pipeline optimization.
• Experience building end-to-end ML systems from preprocessing to deployment.
• Familiarity with MLOps tools such as MLflow, Weights & Biases, Docker, Kubernetes, or Airflow.
• Experience with transformer-based models, diffusion models, or large language models.
• Strong analytical mindset for evaluating performance, generalization, and bias.

Nice to Have

• Experience in a research-driven AI team.
• Knowledge of advanced ML techniques and algorithms.

What We Offer

• Fully remote position with flexible working hours.
• Weekly payments via Stripe or Wise.
• Opportunity to work on cutting-edge AI projects.
• Potential for project extensions based on performance.
• Collaborative environment with a highly skilled team.