AI/ML Engineering

Role Overview

Daice Labs is hiring a remote AI/ML Engineer (United States). You will design, implement, and deploy machine learning models and AI systems across core product and research infrastructure, covering the full ML lifecycle from data pipelines to production deployment.

Responsibilities

• Design and implement ML models for production deployment, including:
  • training pipelines
  • evaluation frameworks
  • inference optimization
• Build and maintain data pipelines for preprocessing, feature extraction, and dataset management
• Integrate components of a hybrid AI architecture spanning symbolic and neural approaches
• Collaborate with research scientists to translate theoretical frameworks into working software
• Write clean, tested, and well-documented code; follow software engineering best practices
• Participate in code reviews, architecture discussions, and sprint planning
• Monitor and improve production model performance, latency, and computational efficiency

Requirements

• BS or MS in Computer Science, Machine Learning, Data Science, or related field
• 3+ years of professional experience in ML engineering or applied AI
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Experience building and deploying ML models in production
• Familiarity with cloud infrastructure (AWS, GCP, or Azure)
• Experience with data processing tools and relational/non-relational databases
• Understanding of software engineering practices (version control, testing, CI/CD)
• Strong written and verbal communication skills

Preferred Qualifications

• Experience with LLMs, transformer architectures, or agentic AI systems
• Familiarity with neurosymbolic AI, knowledge graphs, or formal methods
• Experience with Docker and Kubernetes (or containerized deployment)
• Contributions to open-source ML projects or published research