Senior Machine Learning Operations Engineer

As the most trusted global leader in data-first contract lifecycle management (CLM) software, Agiloft helps organizations manage the end-to-end process of proposing, negotiating, signing, and leveraging contracts using our flexible Data-first Agreement Platform (DAP). With contract data as the foundation, customers quickly and collaboratively reach agreement and leverage contract visibility to thrive with competitive advantage. Employing powerful, pragmatic artificial intelligence as a legal force multiplier, and robust integration capabilities as a data liberator, organizations around the world trust Agiloft’s certified implementers to deliver connected, intelligent, and autonomous solutions across the entire contract lifecycle.

Top analysts like Gartner, Forrester, and IDC agree, all showing Agiloft as a leader in the CLM space. Our no code platform is easily managed and administered by business users, which is why Agiloft is the contract you keep: nearly a full 100% of new customers are satisfied with their initial implementations, and some 97% of customers renew every year. Ours is a growing, vibrant, successful company that is at the forefront of a market that is becoming a must-have for all organizations.

We believe that the way to build the strongest, most vibrant place to work is to bring in individuals from all walks of life, and to support them in bringing their authentic selves to their day, every day. Our working philosophy is that “EX = CX”: when employee experience is excellent, so is customer experience. We support multiple Employee Resource Groups (ERGs), and offer a working environment that supports healthy work/life balance, including floating holidays and a quarterly, no-questions-asked wellness day.

Position Overview

We are looking for a skilled Senior MLOps Engineer to join our growing efforts in machine learning and generative AI. In this role, you’ll collaborate with Data Scientists, Legal Knowledge Experts, Developers, and other MLEs to design, build, and maintain robust production machine learning infrastructure and tooling. You will play a key role in enabling scalable, efficient, and reliable delivery of customer facing machine learning solutions.

• Collaborate with cross-functional teams to build and maintain end-to-end machine learning pipelines, from data ingestion to model deployment and monitoring
• Design, implement, and optimize infrastructure for rapid prototyping, continuous integration, deployment, and model evaluation.
• Monitor and maintain production machine learning systems to ensure reliability, scalability, and performance
• Provide technical guidance and mentorship to junior team members and foster knowledge sharing within the MLOps and Data Science teams
• Stay updated with the latest advancements in MLOps, cloud technologies, and generative AI to identify and implement best practices
• Set and enforce standards for code quality and best practices across the data science and engineering organizations to ensure maintainability, scalability, and robustness of systems.
• Other duties as assigned

• Proven experience deploying and maintaining machine learning models in production environments
• Demonstrated ability to gather requirements, design systems, and scope and plan projects effectively, with a focus on the entire machine learning lifecycle
• Experience with REST API design and implementation, preferably using frameworks such as Flask or FastAPI
• Proficiency in Python, including both general-purpose programming and machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar
• Experience in building and scaling machine learning pipelines and infrastructure, including data gathering, feature engineering, model training, and deployment workflows
• Proficiency with cloud platforms, preferably AWS, and tools like SageMaker, Lambda, or similar
• Strong communication skills to effectively collaborate with diverse teams, including product managers, engineers, and data scientists
• Familiarity with CI/CD tools and practices as they apply to machine learning workflows
• Experience with modern containerization tools such as Docker and Kubernetes

Ensuring a diverse and inclusive workplace is our priority. We are committed to an environment of acceptance where you are free to bring your full self to work. All employment decisions at Agiloft are based on business needs, job requirements, and individual qualifications without regard to race, color, religion or belief, national or social ethnic origin, sex, age, sexual orientation, gender identity and/or expression, parental status, marital status, Veteran status, or any other status protected by the laws or regulations in the locations where we operate. If you have a need that requires accommodation during the recruiting process, please let us know by contacting Director, Talent Acquisition, Brad Toothman at brad.toothman@agiloft.com.

Applicants from underrepresented groups such as minorities, veterans, or individuals with disabilities encouraged to apply.

Applications will be reviewed as submitted. There will be no application deadline for this opportunity.