Machine Learning Engineer

International Recruiting LLC • San Jose, CA

8d

About The Position

The Machine Learning Engineer will help build Max VLM, a video foundation model designed to understand human activities, object interactions, and the physical world through first-person video. The team develops video-understanding systems that interpret complex real-world activities and convert continuous visual observations into structured, actionable information.

The role spans the machine-learning lifecycle, including data collection and generation, model training and fine-tuning, evaluation, optimization, and production deployment. Technical work includes video-language modeling, fine-grained action recognition, temporal grounding and reasoning, long-video comprehension, multimodal post-training, data selection and automated labeling, distributed training, efficient video processing and inference, model compression and quantization, production serving and monitoring, and agentic video understanding. The engineer will also explore reinforcement learning and other advanced post-training techniques, applying useful research to practical product problems.

The position requires a relevant degree or equivalent practical experience, strong deep-learning knowledge, hands-on model experience, Python and PyTorch proficiency, and familiarity with modern language, multimodal, or computer-vision models. Preferred qualifications include impactful research, video or vision-language experience, post-training, distributed training or production ML experience, and familiarity with agentic AI and multimodal reasoning.

Requirements

• Bachelor's, Master's, or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, or equivalent practical experience.
• Strong understanding of deep learning and hands-on experience with model training, fine-tuning, or inference.
• Proficiency in Python and deep-learning frameworks such as PyTorch.
• Familiarity with modern LLMs, multimodal models, or computer-vision models.
• Strong problem-solving skills and the ability to independently implement, debug, and optimize machine-learning systems.
• Ability to work in a fast-paced environment, take ownership, and deliver practical solutions to complex problems.

Nice To Haves

• Strong research capabilities, demonstrated through publications at top-tier conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, or ECCV, or other impactful research contributions.
• Experience with video understanding, vision-language models, or multimodal foundation models.
• Experience with LLM/VLM post-training, including SFT, reinforcement learning, or reasoning-oriented training.
• Experience with distributed training, efficient inference, or production-scale machine-learning systems.
• Familiarity with agentic AI, tool-augmented reasoning, or multimodal reasoning.
• Proven ability to translate novel research ideas into practical implementations and measurable improvements.

Responsibilities

• Design, train, fine-tune, and optimize video-language foundation models for real-world applications.
• Build and improve large-scale machine-learning pipelines for data processing, training, evaluation, and inference.
• Analyze model failures, identify performance bottlenecks, and drive improvements through data and algorithmic iteration.
• Develop efficient model inference and deployment solutions that balance quality, latency, and computational cost.
• Collaborate with product and engineering teams to translate business requirements into technical solutions and deliver production-ready machine-learning capabilities.
• Explore and evaluate emerging techniques in multimodal learning, reinforcement learning, and agentic AI, applying promising advances to practical problems.
• Own machine-learning projects from problem definition and experimentation through deployment and ongoing improvement.

What This Job Offers

• Job Type: Full-time