xAI is looking to develop cutting-edge ML solutions to ensure compliance with X's Terms of Service and enhance user safety by detecting and mitigating threats like abuse, spam, and fraud.
Requirements
- Proven experience managing the full ML lifecycle, from data preparation to model serving
- Familiarity with modern data pipelines and ML infrastructure ecosystems
- Enjoyment of 0-to-1 environments, where you trailblaze novel ML solutions
- Experience applying LLMs to real-world problems, such as natural language understanding or anomaly detection
- Fluency in Python, with knowledge of ML libraries (e.g., TensorFlow, PyTorch)
- Background in scalable systems for handling large datasets
Responsibilities
- Own the end-to-end machine learning lifecycle for safety systems, including data gathering, cleaning, model training, evaluation, and serving at scale
- Develop ML models to detect and remediate violative content in areas like abuse, spam, and child safety
- Integrate models into production systems for real-time inference and high-throughput processing
- Apply creative problem-solving to build novel ML solutions in uncharted spaces
- Collaborate across engineering, product, and operations to enhance the safety ecosystem
- Lead technical initiatives in ML-driven areas like fraud detection or content moderation
Other
- 5+ years in machine learning engineering or related roles
- Prior experience in Trust and Safety or applying ML to content moderation
- All engineers are expected to have strong communication skills.
- They should be able to concisely and accurately share knowledge with their teammates.
- Work ethic and strong prioritization skills are important.
