Advanced ML Engineer

Are you looking for a hybrid or remote work opportunity? Are you interested in a workplace that allows for flexibility in your day? Are you ready for a workplace that provides benefits that suit your needs?
About 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 focus on helping our users discover the truth more quickly, and act on data.  About the Machine Learning (ML) Engineering Role The Machine Learning Engineer is an MLOps-focused role that will work with the data scientists and product teams within the AI group to deploy machine learning solutions at scale. You will help build a platform to support our team and organization in deploying, validating, and monitoring machine learning models at a petabyte scale. You will report to the Manager of Software Engineering. 

Your Role In Action

• Contribute throughout all service lifecycle phases from conception through development, deployment, and operation. 
• Contribute to and mature existing, automated CICD workflows. 
• Participate in code reviews for projects written by your team. 
• Work with our data scientists, product managers, and engineering teams to bring ML feature ideas to proof of concepts and feature planning for projects. 
• Prove out the use of new technology with compelling proof of concepts and demonstration. 
• Work on solutions to improve our model training pipelines, model governance, and model monitoring. 
• Interact with our Customer Support Teams regularly and reduce the operational burden to our customers and keep the team focused on feature delivery during most of their work time. 
• Escalate risks and issues to management proactively so better planning for mitigation and resolution of those can be done. 
• Follow the industry's best engineering practices and use the latest tech stack to implement and deliver code artifacts. 
• Help product teams and clients by releasing applications and services with elite dev ops metrics and creating a smooth customer experience during each release. 
• Demonstrate work completed frequently to product, management, and leadership so feedback can be collected early and planning can be improved continuously. 
• Collaborate with Lead, staff, and principal engineers to develop high availability, scalability, and reliability solutions. 
• Mentor interns within the AI group to promote career development. 

Your Skills

• Knowledge of data ingestion, cleansing, analyzing, and feature extraction operations. 
• Experience in using Machine Learning Libraries like TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas, etc. when Python is used to implement ML solutions. 
• Experience training and deploying machine learning models. 
• Experience in performance testing of machine learning models and generating useful metrics for the engineering and product teams. 
• Experience in deploying machine learning models from the local environment to production. 
• Experience monitoring data and models through the complete ML lifecycle with end-to-end lineage. 
• Experience designing APIs, service-oriented architectures, and cloud-based distributed systems. 
• Fluent in programming languages suitable to implement machine learning solutions. Ex: Python or Scala. 
• Experience working with single-cloud or multi-cloud environments to deploy, secure, and scale applications and services. Ex: Azure, AWS, GCP 
• Experience in Job Orchestration workflows and Job Running Frameworks in the cloud. Ex: Prefect, Apache Airflow, Spark, Databricks.  

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 plans Parental leave for primary and secondary caregivers Flexible work arrangements Two, week-long company breaks per yearUnlimited time off Long-term incentive program Training investment program
Transparency in Coverage InformationThe Transparency in Coverage Final Rule requires disclosure of the negotiated rates with in-network providers and the historic allowed amounts paid to out-of-network providers, for all health plans available to employers. Files containing this information for the plans covered are published on this page.Link: https://www.bcbsil.com/asomrf?EIN=123456789
All 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.