Staff AI Engineer

Posting Type

Hybrid/Remote

Job Overview

Job Description and Requirements

• Build trusted AI solutions that improve user experiences, products, investigations, and legal matters.
• Develop world-class tools to solve complex challenges through experimentation and innovation.
• Leverage AI across all stages of the discovery lifecycle to improve outcomes and optimize product operations.
• Invest in modern data infrastructure, data pipelines, and data lake technologies that enable large-scale AI and analytics.
• Foster a culture of exploration, experimentation, continuous learning, and innovation.

• Define and evangelize the multi-year technical roadmap for ML Ops, aligning platform architecture with product and research objectives.
• Provide technical direction and mentorship across multiple engineering teams and organizations.
• Drive the design and architecture of training, inference, and monitoring systems focused on scalability, extensibility, performance, and reliability.
• Partner with product, program, and data science leaders to scope and deliver cross-functional roadmaps.
• Evaluate emerging ML Ops technologies and establish engineering standards and best practices.
• Champion advanced optimization techniques, including sparsity, quantization, and pruning, to improve performance and cost efficiency.
• Collaborate with security teams to maintain strong data protection practices and responsible AI standards.
• Lead architecture reviews, publish engineering best practices, and mentor senior and lead engineers across the organization.

• 8+ years of professional software engineering experience.
• 5+ years of experience working in ML/AI or big data environments.
• 4+ years of technical leadership experience across multiple teams.
• Expert-level proficiency in Python, Java, or Scala for production systems.
• Deep hands-on experience with Docker, Kubernetes/Helm, and infrastructure-as-code tools such as Terraform or Pulumi.
• Proven experience building and operating CI/CD pipelines for machine learning workflows using technologies such as Prefect or Airflow.
• Experience deploying and operating secure, monitored services on AWS, Azure, or GCP.
• Demonstrated ability to mentor senior engineers, influence technical strategy, and drive cross-team initiatives to successful completion.

• Master’s or PhD in Computer Science, Engineering, Mathematics, or a related field.
• Recognized technical thought leadership through open-source contributions, conference presentations, or publications.
• Experience scaling ML platforms utilizing distributed data technologies such as Spark or Kafka.
• Expertise implementing advanced model optimization techniques, including compression, pruning, and quantization, in production environments.

• Build systems that help customers organize data, discover the truth, and act on it in high-stakes legal matters.

• Work on distributed, cloud-native systems that process large volumes of data.

• Build with AI, cloud platforms, and scalable architectures shaping legal tech.

• Gain experience owning systems end-to-end across cloud and distributed environments.

• Work in a team focused on knowledge sharing and continuous improvement.

• Diverse perspectives create stronger teams and better outcomes.

• Competitive salary, benefits, DTO, parental leave, and equity program.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position. 

Required Skills: