ML Engineer

METEOR — AI platform for communication.

Responsibilities:

• Develop, fine-tune, evaluate, and implement generative models for image, video, text, and multimodal applications.
• Build scalable data, training, evaluation, real-time inference, and MLOps pipelines; optimize latency, throughput, memory usage, quality, and infrastructure costs.
• Integrate models into production systems, automate deployment and monitoring, and research and assess generative AI methods for production use.

Requirements:

• 3+ years of professional machine learning and software development experience
• Practical experience developing or deploying generative AI models
• Deep understanding of diffusion models and modern image or video-generation architectures
• Experience with LLM prompt engineering, fine-tuning, evaluation, structured outputs, tool invocation, and behavior management
• PyTorch or TensorFlow
• Productionizing models and operating reliable inference services
• Deployment on GPU servers and cloud platforms

Optional:

• Experience with preference optimization methods such as RLHF, DPO, or reinforcement learning; constrained decoding, function calling, agent systems, safety mechanisms, red-team testing, and automated LLM evaluation
• Multimodal models
• Video-generation quality improvements
• GPU optimization
• MLOps platforms, model registries, experiment tracking, observability, CI/CD, and infrastructure as code