Machine Learning Azure/devops 🔥
Machine Learning DevOps - Terraform/Ansible/User Credential Passthrough/Azure AD
Contract: 18 month project with desire to hire the candidate after approximately 1 years of work. Candidate must be open to convert to perm.
Client Location: St. Louis, MO
Remote: work Remotely - must be comfortable to be on daily video calls and be recorded for client documentation purposes
Work Status: USC / Green Card (REQUIRED)
Perfect English/Communication skills
This is to help you understand the job > Defined: Machine Learning Ops / MLOps / ML Ops is a set of practices that aims to deploy and maintain machine learning models in production reliably and efficiently. The word is a compound of "machine learning" and the continuous development practice of DevOps in the software field.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Debug complex internal and external infrastructure problems or limitations
- Experienced in Information Technology processes and methodologies
- Work with stakeholders including the business analytics teams and Information Technology architecture teams to assist with systems-related technical issues and support their infrastructure needs.
- Onboards new associates, and mentors associates on established processes and procedures
Project Details - The MLOps Engineer will be assigned to the MLOps Product Delivery Team. The team will function in an Agile Framework. The candidate will have the opportunity to influence processes and procedures for the area since it is a new team and area to Jones.
Team Details - Team currently consists of two MLOps Engineers. The Product Delivery Team consists of a Product Owner, Analyst, Product Delivery Manager, Scrum Master, and two MLOps Engineers. The candidate will be working with Data Scientists and the Technology Platform Team
Required Qualifications
- 3 years of experience in an ML Engineer role
- Experience deploying ML solutions both on-premise and in cloud
- Bachelor's degree in Computer Science, Information Systems or another applicable field is preferred
- Experience building and optimizing ML pipelines using DevOps and CI/CD principles
- Experience training and validating ML pipelines based on model output
- 1 -3 years of experience using at least one the following platforms/technologies:
- Azure or AWS cloud environments
- Connecting to Data Science/Engineering ETL solutions (CDC, Kafka, APIs, ELT)
- Advanced Analytic tools (Dataiku, IBM CPLEX, etc.)
- Code repository and notebook solutions (Git, Jupyter, etc.)
- object-oriented/object function scripting languages (R, Python, Java, Node.js)
Preferred Qualifications
- Experience working in Agile
- Experience working with Dataiku
This is a remote position.