Machine Learning Operations Engineering Lead (Remote)

Key Skills

AWS, AWS Sagemaker, Deep Learning, Docker, Kubernetes-K8s, Machine learning techniques, MLOps tools, Pandas, Python Programming, Scikit-learn, XGBoost

Job Description

Agiloft was named a Leader in the 2023 Gartner Magic Quadrant for Contract Life Cycle Management for the fourth year in a row. Contract Lifecycle Management (CLM) is one of the fastest-growing areas of enterprise sales, with a TAM projected to climb from $2B to $7B in the next 5 years.

The Agiloft Contract Lifecycle Management platform has won dozens of awards, including the Editor's Choice award from PC Mag, for the past five years in a row.

Agiloft has a highly differentiated value proposition which is uniquely appealing to enterprises: pre-built applications with a deeply configurable, no-code platform for integrated Business Process Management throughout an organization.

Agiloft is pioneering the applied use of Artificial Intelligence to enable next-generation business commerce at organizations ranging from small enterprises to U.S. government agencies and Fortune 100 companies.

Additionally, 99% of employees who commented on Glassdoor would recommend Agiloft to a friend.

Position Overview

We are looking for an experienced Machine Learning Engineer and leader 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 gen AI space.

Job Responsibilities

• You’ll serve as a team lead, manager and mentor to a small 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 gen AI 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

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 brad.toothman@agiloft.com.

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