AI Research Engineer

Relari, inc.

San Francisco (CA)

Presencial

USD 125 000 - 185 000

Tempo integral

Há 4 dias
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Resumo da oferta

Relari, inc. in San Francisco develops machine learning systems for dexterous robotic manipulation. We seek engineers who turn research ideas into working systems, spanning data processing, training, evaluation, and real-world deployment.

You will design and optimize training pipelines, build scalable infrastructure, and collaborate with robotics engineers to deploy models on physical robots using feedback from real-world use.

Qualificações

  • Strong Python programming skills and experience with ML frameworks.
  • Deep learning, model training, optimization, and evaluation fundamentals.
  • Experience building ML systems beyond APIs and pretrained models.

Responsabilidades

  • Develop and improve training pipelines for models using human and sensor data.
  • Train and adapt models for manipulation and imitation learning.
  • Explore representations from vision, motion, and signals.
  • Experiment with imitation learning, RL, and foundation models for robotics.
  • Design experiments to understand model behavior and improvements.
  • Build scalable data processing, training, and evaluation infrastructure.
  • Collaborate with robotics engineers to deploy models on physical robots.

Conhecimentos

Python
PyTorch
JAX
Deep learning
Experiment design
ML infrastructure
Robotics
Computer vision

Descrição da oferta de emprego

You will develop machine learning systems that enable robots to acquire dexterous manipulation skills from human demonstrations and multimodal sensor data. You will work across data processing, model training, evaluation, and real-world deployment, using experiments to understand what makes robots learn more effectively. Our research involves vision, motion, biomechanical signals, and robot interaction data, with applications to imitation learning, vision-language-action models, video models, and world models. We are looking for engineers with strong machine learning fundamentals and the ability to turn research ideas into working systems. Prior robotics experience is not required.

What you'll do
  • Develop and improve training, fine-tuning, and evaluation pipelines for machine learning models using human and robot data.
  • Train and adapt models for manipulation, action prediction, and learning from demonstrations.
  • Explore methods for learning representations from vision, motion, and biomechanical signals.
  • Experiment with imitation learning, reinforcement learning, and modern foundation models for robotic applications.
  • Design experiments and ablations to understand model behavior, identify limitations, and measure improvements.
  • Build scalable data processing, training, and evaluation infrastructure to support rapid experimentation.
  • Work with robotics engineers to deploy models on physical robots, analyze failures, and improve performance using real-world feedback.
  • Read and reproduce relevant research, adapting promising methods to new problems.
What we're looking for
  • Strong programming skills in Python and experience with PyTorch, JAX, or similar machine learning frameworks.
  • Solid understanding of deep learning, model training, optimization, and evaluation.
  • Experience developing and evaluating machine learning systems beyond using pretrained models through APIs.
  • Ability to independently design experiments, debug training pipelines, and interpret results.
  • Experience in one or more areas such as computer vision, multimodal learning, generative models, representation learning, reinforcement learning, or imitation learning.
  • Experience with large-scale training, distributed computing, or ML infrastructure is a plus.
  • Experience with robotics, VLA models, video models, or world models is a plus, but not required.
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