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Posting Type
Hybrid/Remote
Job Overview
WHO WE ARERelativity is a leading legal data intelligence company building technology that helps users organize data, discover the truth, and act on it with confidence. Our AI-powered, cloud platform, RelativityOne, transforms massive volumes of complex information into actionable insights for litigation, investigations, regulatory inquiries, data breach responses, and other high-stakes legal work where accuracy and trust are crucial.
The world’s largest law firms, corporations, and government agencies rely on Relativity’s legal AI software to securely surface and manage the most relevant and impactful information in their matters. Beyond our commercial impact, we are committed to expanding access to technology and supporting pro bono legal work.
WHAT WE DO
Our AI team is focused on helping users discover the truth more quickly and act on data with confidence through AI-powered innovation. We are committed to algorithm excellence, building trusted and scalable AI solutions that improve user experiences, products, investigations, and operational efficiency.
Relativity’s AI and Data Science teams leverage large-scale datasets, modern data infrastructure, and advanced machine learning technologies to deliver insights at scale. Our engineers and data scientists collaborate to build secure, high-performing platforms that support experimentation, innovation, and continuous improvement across the AI lifecycle.
Job Description and Requirements
- Contribute to the design and implementation of ML/AI platforms with a focus on scalability, reliability, security, and standardized GenAI workflows.
- Partner with data scientists, product managers, security teams, and data engineers to deliver high-impact machine learning solutions.
- Implement and improve CI/CD pipelines for machine learning models and data workflows using containerization, infrastructure-as-code, and orchestration technologies.
- Build and enhance automated model training, deployment, and lifecycle management processes.
- Prototype and evaluate emerging MLOps technologies to improve efficiency, optimize costs, and enable new product capabilities.
- Deploy, monitor, tune, and troubleshoot production machine learning models.
- Establish and track health, performance, reliability, and cost optimization metrics for AI systems.
- Participate in code reviews and design reviews while contributing directly to implementation efforts.
- Mentor junior engineers and share best practices across the engineering and AI organizations.
- Continuously learn and apply new technologies, tools, and techniques to improve the AI platform.
- 3+ years of professional software engineering experience, including at least 1 year working in ML/AI or big data environments.
- Proficiency in Python, Java, or C#.
- Production experience using Docker.
- Experience deploying cloud-based solutions on AWS, Azure, or GCP.
- Experience using infrastructure-as-code tools such as Terraform or Pulumi.
- Familiarity with workflow orchestration platforms such as Prefect, Airflow, or similar technologies.
- Understanding of Kubernetes and Helm fundamentals.
- Experience deploying, monitoring, and troubleshooting machine learning models in production environments.
- Ability to collect and analyze metrics related to model reliability and algorithm health.
- Strong collaboration and communication skills with cross-functional stakeholders.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Master’s degree in a relevant discipline.
- Experience with ML lifecycle platforms such as MLflow or Kubeflow.
- Experience with model optimization techniques including quantization, pruning, or compression.
- Exposure to distributed data processing technologies such as Spark, EMR, or Kafka.
- Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
- Experience working in secure and compliant data processing 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:
$103,000 and $155,000The 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:
Engineering Principle, Hardware Integration, Innovation, Problem Solving, Process Improvements, Quality Assurance (QA), Research and Development, System Designs, Technical Documents, TroubleshootingSkills Required
- 3+ years of professional software engineering experience, including at least 1 year in ML/AI or big data environments
- Proficiency in Python, Java, or C#
- Production experience using Docker
- Experience deploying cloud-based solutions on AWS, Azure, or GCP
- Experience with infrastructure-as-code tools such as Terraform or Pulumi
- Familiarity with workflow orchestration platforms such as Prefect or Airflow
- Understanding of Kubernetes and Helm fundamentals
- Experience deploying, monitoring, and troubleshooting machine learning models in production
- Ability to collect and analyze model reliability and algorithm health metrics
- Strong collaboration and communication skills with cross-functional stakeholders
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field
- Master's degree in a relevant discipline
- Experience with ML lifecycle platforms such as MLflow or Kubeflow
- Experience with model optimization techniques including quantization, pruning, or compression
- Exposure to distributed data processing technologies such as Spark, EMR, or Kafka
- Familiarity with deep learning frameworks such as TensorFlow or PyTorch
- Experience working in secure and compliant data processing environments
Relativity Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Relativity and has not been reviewed or approved by Relativity.
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Leave & Time Off Breadth — Time off options include discretionary time off and two company‑wide breaks each year, providing additional recharge time.
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Healthcare Strength — Health coverage includes comprehensive medical, dental, and vision plans, telehealth access, and wellness resources such as a Headspace subscription.
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Parental & Family Support — North America offers up to 12 weeks of fully paid parental leave, with comparable regional programs in EMEA and APAC.
Relativity Insights
What We Do
At Relativity, we build innovative and comprehensive tools for making sense of unstructured data. When more people can find the facts in mountains of documents, emails, and texts, more legal and data-centric matters can be resolved equitably. Join us in our mission to help our customers organize data, discover the truth, and act on it. Relativity makes software to help users organize data, discover the truth and act on it. Its SaaS product, RelativityOne, manages large volumes of data and quickly identifies key issues during litigation and internal investigations. Relativity has more than 300,000 users in approximately 40 countries serving thousands of organizations globally primarily in legal, financial services and government sectors, including the U.S. Department of Justice and 198 of the Am Law 200. Relativity does not tolerate racism or discrimination of any kind. We do not accept unfair treatment of any person or group of people. We’re committed to advocating for change to make our world a more inclusive, just place.
Why Work With Us
We believe in our team members and we want to help you own your career as part of a community of values-driven people who help customers around the world solve complex data challenges. At Relativity, you’ll take on challenging work, but you’ll also partner with talented colleagues and pursue plenty of learning and development opportunities.
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