Member of Technical Staff, Model Training

Crossing Hurdles; United States; Remote; USD 600.000 - 1.800.000; Vollzeit

Zusammenfassung

Crossing Hurdles is seeking a Member of Technical Staff, Model Training, to advance AI models in a remote, flexible setting. You will train, fine-tune, and optimize language and multimodal models, collaborating with research and platform teams to deliver production-ready deployments.

Ideal candidates have strong ML foundations and hands-on experience with LLMs, vision-language models, robotics, and reinforcement learning, with proficiency in Python and PyTorch.

Qualifikationen

• Strong foundations in machine learning and deep learning with hands-on experience training, adapting, and evaluating modern AI models.
• Practical experience in large language models, vision-language models, robotics, reinforcement learning, or autonomous agents.
• Strong proficiency in Python and PyTorch, with the ability to develop reliable training, evaluation, and inference pipelines.
• Solid software engineering fundamentals for production-ready research prototypes.

Aufgaben

• Train, fine-tune, and adapt language, vision-language, and robotics models using supervised fine-tuning, RL, imitation learning, and distillation.
• Develop specialized models for multimodal understanding and autonomous agents.
• Build simulation-based training/evaluation environments to study policy learning and task generalization.
• Combine expert demonstrations, human feedback, synthetic datasets, and trajectories into training data.
• Optimize models for production inference balancing quality, latency, throughput, and efficiency.
• Collaborate with research and platform teams to transition prototypes to production-ready deployments.

Kenntnisse

Machine learning

Deep learning

LLMs

Robotics

Reinforcement learning

Tools

Python

PyTorch

Jobbeschreibung

Position:

Member of Technical Staff, Model Training

Type:

Full-time

Compensation:

$600000 - $1800000/yr

Location:

Remote

Commitment:

10-40 hrs/week

Role Responsibilities

• Train, fine-tune, and adapt language, vision-language, and robotics models using supervised fine-tuning, reinforcement learning, imitation learning, and distillation.
• Develop specialized models for complex applications, including multimodal understanding, robotic perception and control, and autonomous agents.
• Build simulation-based training and evaluation environments to study policy learning, task generalization, and capability transfer.
• Combine expert demonstrations, human feedback, synthetic datasets, and environment-generated trajectories into effective training datasets.
• Optimize models for production inference, balancing quality, latency, throughput, and computational efficiency.
• Collaborate with research and platform engineering teams to transition prototypes into scalable, production-ready model deployments.

Requirements

• Strong foundations in machine learning and deep learning with hands-on experience training, adapting, and evaluating modern AI models.
• Practical experience in large language models, vision-language models, robotics, reinforcement learning, or autonomous agents.
• Strong proficiency in Python and PyTorch, with the ability to develop reliable training, evaluation, and inference pipelines.
• Experience translating application requirements into measurable model objectives, benchmarks, and performance improvements.
• Solid software engineering fundamentals, including the ability to build maintainable systems and move research prototypes toward production.