Staff AI Software Engineer

Job OverviewAbout AI at Relativity In the past two years, billions of documents have already benefited from the insights of Relativity AI – and we are just getting started on our journey to use AI to improve each user experience, product, matter, and investigation at Relativity. We are focused on helping our users discover the truth more quickly, and act on data with confidence. - We are focused on algorithm excellence, to provide the most robust and trusted experience possible. - We are creating a world-class toolset to solve complex challenges quickly and iteratively. - AI will be leveraged everywhere, in all stages of the discovery process to better manage cases and to optimize product operations. As a team, we believe in exploration, experimentation, and bringing your curiosity to work every day. We know that you can’t innovate without experimentation — and a little failure happens on the path to invention. We use the latest and greatest to ensure we are the best. We strive to experiment, ship, and learn every day. About Data Science at Relativity Relativity’s scale and breadth create tremendous variety for rich data exploration and insights; our market position and scaled products mean our models and insights can quickly be in the hands of our users. Great insights can’t happen without great data, and the best insights come from massive data. Our data infrastructure and engineering ensure that the breadth of Relativity data is available for insights, confidential data is kept confidential, data is always protected, and we are investing heavily in data-pipeline and data-lake technology moving forward. If you’re looking for a data-rich environment that is already heavily using AI, with at-scale challenge and a ton of innovation and experimentation ahead, you will find yourself at home on the AI team within Relativity. About the Staff AI Engineer Role Staff AI Engineers at Relativity operate as domain architects and strategic accelerators. You will work across multiple engineering and data-science teams, defining the long-term vision for Relativity’s ML platform, guiding high-impact projects from concept to production, and ensuring that our AI capabilities remain secure, reliable, and cost-effective at global scale.Job Description and RequirementsResponsibilities Technical Vision & Strategy. Define and evangelize the multi-year technical roadmap for ML Ops, aligning platform architecture with product and research needs. Cross-Team Leadership. Provide technical direction and mentorship across several engineering squads—an evolution of the senior expectation to “work with a team of engineers” and the lead mandate to “lead a team of engineers” . Platform Architecture Ownership. Drive the design of training, inference, and monitoring systems that meet demanding timelines, extensibility, performance, and scale goals. Program Management. Partner with product, program, and science leaders to scope and deliver cross-functional roadmaps, minimizing risks and maximizing opportunities. Innovation & Standards. Evaluate emerging ML Ops tooling, establish engineering standards, and champion advanced optimization techniques (sparsity, quantization, pruning) for cost and performance gains. Governance & Compliance. Collaborate with security teams to uphold robust data protection and responsible AI practices at scale. Community & Mentorship. Foster a culture of learning by leading architecture reviews, publishing best practices, and mentoring senior and lead engineers organization wide. Minimum Qualifications 8+ years of professional software engineering experience, including 5+ years in ML/AI or big-data environments and 4+ years of technical leadership 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 track record building and operating CI/CD pipelines for ML workflows (e.g., Prefect, Airflow) and deploying secure, monitored services on AWS, Azure, or GCP. Demonstrated ability to mentor senior engineers, influence technical direction, and drive cross-team initiatives to completion. Preferred Qualifications Master’s or PhD in Computer Science, Engineering, Mathematics, or related field. Recognized thought leadership through open-source contributions, conference talks, or publications. Experience scaling ML platforms that leverage distributed data frameworks such as Spark or Kafka. Expertise in implementing advanced model-optimization techniques (compression, pruning, quantization) in production environments. Relativity is a diverse workplace with different skills and life experiences—and we love and celebrate those differences. We believe that employees are happiest when they're empowered to be their full, authentic selves, regardless how you identify.Benefit Highlights:Comprehensive health, dental, and vision plansParental leave for primary and secondary caregiversFlexible work arrangementsTwo, week-long company breaks per yearAdditional time offLong-term incentive programTraining investment programAll qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.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:300 000 and 450 000PLNThe 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.