Member of Technical Staff, Model Training (Applied Research)

Location: Remote, US

Salary: $200,000–$320,000 base salary per year

Company

hirify.global develops specialized AI models and a flow ecosystem for data generation, annotation, quality assurance, and automated grading.

What you will do

• Train, fine-tune, and adapt language, vision-language, robotics, and autonomous-agent models using SFT, reinforcement learning, imitation learning, and distillation.
• Develop models for multimodal understanding, robotic perception and control, reasoning, planning, and tool use.
• Build simulation-based training and evaluation environments for policy learning, task generalization, and sim-to-real transfer.
• Combine expert demonstrations, human feedback, synthetic data, and environment-generated trajectories into training datasets, reward signals, and learning curricula.
• Improve data generation, annotation, quality assurance, automated grading, accuracy, robustness, and task success through iterative feedback-driven training.
• Optimize models for production inference and collaborate with research and platform engineering teams to deploy scalable systems balancing quality, latency, throughput, and cost.

Requirements

• Strong foundations in machine learning and deep learning, with hands-on experience training, adapting, and evaluating modern AI models.
• Practical experience with one or more of large language models, vision-language models, robotics, reinforcement learning, or autonomous agents.
• Strong proficiency in Python and PyTorch, including reliable training, evaluation, and inference pipelines.
• Experience translating application requirements into measurable model objectives, benchmarks, and performance improvements.
• Solid software engineering fundamentals and the ability to move research prototypes toward maintainable production systems.
• Familiarity with fine-tuning, distillation, imitation learning, or reinforcement learning.
• Strong experimental judgment, including independently identifying bottlenecks, evaluating trade-offs, and iterating toward effective solutions.

Nice to have

• Experience with robotics, embodied AI, vision-language-action models, or simulation-based policy learning.
• Familiarity with agent frameworks, tool-using models, and environment-driven training.
• Experience with synthetic data generation, human-in-the-loop learning, or automated evaluation systems.
• Knowledge of quantization, batching, model compression, and efficient serving.
• Experience deploying specialized models in production with demanding latency, reliability, or cost requirements.
• Research contributions or open-source work in applied machine learning, multimodal AI, robotics, or agent systems.

Culture & Benefits

• Full-time, remote-first position.
• Equity compensation and potential performance-based bonuses.
• Health-insurance premiums reimbursed up to 100%.
• Paid time off and a 401(k) plan with company match.
• AI tools assist with candidate screening and assessment while human decision-making remains part of the process.