Machine Learning Engineer, AI Safety

Ladders; United States; Remote; USD 124,000 - 242,000; Full time

Benefits offered by this job

Equity opportunities

Comprehensive benefits package

Job summary

Ladders is seeking a Machine Learning Engineer, AI Safety to join our client’s team in the telecommunications and hardware space. This role focuses on building and evaluating ML systems for content safety, model robustness, and responsible AI, partnering with engineers, data scientists, and researchers to strengthen behavior and safety metrics.

The position offers remote work for US-based candidates and a compensation range of $124,000 to $241,500 annually, with equity opportunities and a

Qualifications

• Master’s or PhD in computer science, electrical engineering, or related field, or equivalent experience.
• 2+ years of experience deploying machine learning models in production.
• Strong understanding of machine learning principles and algorithms.
• Hands-on programming in Python and ML frameworks such as PyTorch or Keras.
• 1+ year of experience in content safety, ML fairness, robustness, or related fields.

Responsibilities

• Develop datasets and models for training and evaluating LLMs for content safety, product security, robustness, and ML fairness.
• Research bias detection and mitigation techniques in LLMs and related systems.
• Define and track metrics for responsible LLM behavior and usage.
• Adhere to MLOps best practices in automation, monitoring, scale, and safety.
• Contribute to the MLOps platform and develop tools for ML team effectiveness.
• Collaborate with engineers, data scientists, and researchers on content safety and ML fairness solutions.

Skills

Python

ML fundamentals

MLOps

Content safety

Education

Master’s or PhD in CS/EE or related

Tools

PyTorch

Keras

Job description

For our client, we are seeking a Machine Learning Engineer, AI Safety to join the team of a leader in the Telecommunications & Hardware space.

This role will focus on building and evaluating machine learning systems that support content safety, model robustness, and responsible AI practices. You will partner closely with engineers, data scientists, and researchers to strengthen model behavior, improve safety metrics, and scale reliable machine learning operations. The position also offers the opportunity to contribute to tools and platform capabilities that improve team effectiveness across the ML lifecycle.

Location: Remote - US based candidates only, no visa sponsorship available

Compensation: $124,000 - $241,500 annually

Responsibilities

• Develop datasets and models for training and evaluating LLMs for content safety, product security, robustness, and ML fairness
• Research bias detection and mitigation techniques in LLMs and related systems
• Define and track metrics for responsible LLM behavior and usage
• Adhere to MLOps best practices in automation, monitoring, scale, and safety
• Contribute to the MLOps platform and develop tools for ML team effectiveness
• Collaborate with engineers, data scientists, and researchers on content safety and ML fairness solutions

Qualifications

• Master’s or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience
• 2+ years of experience deploying machine learning models in production
• Strong understanding of machine learning principles and algorithms
• Hands-on programming experience in Python and knowledge of ML frameworks such as Keras or PyTorch
• 1+ year of experience in content safety, ML fairness, robustness, AI model security, or related fields
• Familiarity with challenges in hate, harassment, or other harmful content areas within content safety
• Experience with large multi-modal datasets and models

Benefits

• Eligible for equity opportunities
• Access to a comprehensive benefits package

Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification - your background could be exactly what this team needs.