Manager, MLOps Engineering

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 an experienced Machine Learning Engineer Manager to join our growing efforts in machine learning and generative AI. You’ll lead our MLOps team within Data Science, working with our Data Scientists, Knowledge Experts and Developers to build a first class production machine learning infrastructure to support our customers’ models and our advanced internal development using a variety of cutting edge approaches in the deep learning and the genAI space.

Job Responsibilities

• You’ll serve as a team lead, manager and mentor to a team of Machine Learning Engineers tasked with MLOps
• Working with our Data Science and Engineering teams, you will help build production features that leverage our machine learning and genAI technologies
• You will develop infrastructure and process for rapid machine learning prototyping, continuous deployment, and evaluation with customers
• You will help develop and support our platform for out of the box and custom trained customer AI models
• You’ll participate in large-scale project planning and stakeholder education
• Other duties as assigned

A little bit about you...

• 5 or more years experiencing with MLOps or Machine Learning Engineering
• Experience leading major projects and mentoring junior team members
• You have experience deploying machine learning models in production, and building production infrastructure
• You can communicate clearly and empathetically with developers, product managers, and UX designers to explain the abilities and limitations of ML systems
• Programming with Python and the associated data science/machine learning stack (e.g. scikit-learn, pandas, xgboost)
• Experience with deep learning and genAI models, both third party and open source preferred
• Experience with cloud infrastructure, preferably AWS and Sagemaker
• 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 [email protected].

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.