Sr Machine Learning Ops Engineer

Overview

Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models.

Partner with Data Scientists to help use the foundational platform upon which models can be built and trained. Operationalize ML Models at scale (e.g. serve predictions on tens of millions of customers). Explore new technology trends and leverage them to simplify our data and ML ecosystem. Build tools to help detect shifts in data/features used by ML models to identify issues in advance of deteriorating prediction quality, monitor the uncertainty of model outputs, and automate prediction explanation for model diagnostics.

Drive innovation and implement solutions with future thinking. Guide teams to improve development agility and productivity. Resolve technical roadblocks and mitigate potential risks. Deliver system automation by setting up continuous integration/continuous delivery pipelines.

Location:

Durham, North Carolina | Job type:
Contract | Salary: $79 - 80 per hour |

Work hours:

8am to 5pm |

Education:

Bachelors

• Has bachelor’s or master’s degree in a technology related field (e.g. Computer Science, Engineering, etc.).
• Proven experience in building cloud-native applications using AWS services including Sage Maker AI, Bedrock, S3, Cloud Formation (CFT), SNS, SQS, Lambda, AWS Batch, Step Functions, Event Bridge, Cloud Watch. Familiarity with Azure Cognitive Services (deploying OpenAI models) and Google Compute Vertex is beneficial.
• Strong experience with CI/CD tools ( Jenkins preferred ), version control (Git), and containerization (Docker). Expertise in IaC (AWS Cloud Formation, Terraform/Open Tofu) for managing cloud resources.
• Extensive experience with deploying, inference, tuning, and measuring ML models.
• Strong knowledge of developing highly scalable distributed systems using open-source technologies.
• 5+ years of experience in developing and implementing Python-based cloud applications and/or ML solutions.
• 1+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sage Maker.
• Proven experience in application hosting on Kubernetes environments.
• Proficiency in Python development with ML ecosystem (numpy, pandas, sklearn, tensor flow, etc.), Linux scripting, and design of software using object-oriented and functional paradigms. Basic knowledge of Java and Groovy is a plus.
• Solid experience in Agile methodologies (Kanban and SCRUM).

• Designing & developing a feature generation & store framework that promotes sharing of data/features among different ML models.
• You have strong technical design and analysis skills.
• You can deal with ambiguity and work in a fast-paced environment.
• You have experience supporting critical applications.
• You are familiar with applied data science methods, feature engineering and machine learning algorithms.
• Your data wrangling experience spans structured, semi-structured, and unstructured data.
• Your experience building ML infrastructure, with a strong focus on software engineering.
• You have excellent communication and collaboration skills to work with multiple teams in the organization.
• You can understand and adapt to changing business priorities and technology advancements in a Data Science and Big Data ecosystem.

Equal Opportunity

Employer:

Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

Accommodation: At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact

Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. Randstad Digital offers a comprehensive benefits package, including medical, prescription, dental, vision, AD&D, and life insurance, short-term disability, and a 401K plan (benefits based on eligibility).

This posting is open for thirty (30) days.