ML Ops Support Engineer

Net2Source Inc.; Reading (Berks County); On-site; USD 88,000 - 141,000; Full time

Job summary

Net2Source Inc. recherche un MLOps L2 Support Engineer pour fournir un support de production 24/7 pour les pipelines ML et les workflows de données. Le candidat travaillera avec Dataiku et AWS pour maintenir des modèles ML en production tout en assurant une disponibilité élevée et une résolution des incidents. Cette fonction exige des compétences en MLOps, Data Engineering et une familiarité avec les outils comme Docker et Jenkins. Les candidats devraient avoir une expérience solide dans la gestion des workflows de données et être capables de travailler sous pression.

Qualifications

• 5+ années d'expérience en MLOps ou en support de production.
• Solide expérience avec Dataiku et AWS.
• Expérience en dépannage et en automatisation.

Responsibilities

• Fournir un support L2 pour les environnements MLOps, en s'assurant de la disponibilité et de la fiabilité.
• Surveiller les journaux et les alertes en utilisant Dataiku et AWS.
• Gérer les déploiements des modèles ML et des pipelines de données.

Skills

MLOps

Data Engineering

Python

Bash

SQL

Monitoring

Incident Response

Education

ITIL/DevOps Certifications

Tools

Dataiku DSS

AWS

Docker

Kubernetes

GitHub Actions

Jenkins

Job description

1 day ago Be among the first 25 applicants

• Rotational on-call support (including weekends and nights).
• Shift-based monitoring for ML workflows and Dataiku jobs.
• Flexible work schedule to handle production incidents and critical ML model failures.

Role:

• MLOps L2 Support Engineer to provide 24/7 production support for machine learning (ML) and data pipelines.
• The role requires on-call support, including weekends, to ensure high availability and reliability of ML workflows.
• The candidate will work with Dataiku, AWS, CI/CD pipelines, and containerized deployments to maintain and troubleshoot ML models in production.

Key Responsibilities:

• Provide L2 support for MLOps production environments, ensuring uptime and reliability.
• Troubleshoot ML pipelines, data processing jobs, and API issues.
• Monitor logs, alerts, and performance metrics using Dataiku, Prometheus, Grafana, or AWS tools such CloudWatch.
• Perform root cause analysis (RCA) and resolve incidents within SLAs.
• Escalate unresolved issues to L3 engineering teams when needed. Dataiku Platform Management:
• Manage Dataiku DSS workflows, troubleshoot job failures, and optimize performance.
• Monitor and support Dataiku plugins, APIs, and automation scenarios.
• Collaborate with Data Scientists and Data Engineers to debug ML model deployments.
• Perform version control and CI/CD integration for Dataiku projects.

Deployment & Automation:

• Deploy ML models and data pipelines using Docker, Kubernetes, or Dataiku Flow.
• Automate monitoring and alerting for ML model drift, data quality, and performance.
• Monitor AWS-based ML workloads (SageMaker, Lambda, ECS, S3, RDS).
• Manage storage and compute resources for ML workflows.
• Support database connections, data ingestion, and ETL pipelines (SQL, Spark, Kafka).

Security & Compliance:

• Ensure secure access control for ML models and data pipelines.
• Support audit, compliance, and governance for Dataiku and MLOps workflows.
• Respond to security incidents related to ML models and data access.

Required Skills & Experience:

• Experience: 5+ years in MLOps, Data Engineering, or Production Support.
• Dataiku DSS: Strong experience in Dataiku workflows, scenarios, plugins, and APIs.
• Cloud Platforms: Hands-on experience with AWS ML services (SageMaker, Lambda, S3, RDS, ECS, IAM).
• CI/CD & Automation: Familiarity with GitHub Actions, Jenkins, or Terraform.
• Scripting & Debugging: Proficiency in Python, Bash, SQL for automation & debugging.
• Monitoring & Logging: Experience with Prometheus, Grafana, CloudWatch, or ELK Stack.
• Incident Response: Ability to handle on-call support, weekend shifts, and SLA-based issue resolution.

Preferred Qualifications:

• Containerization: Experience with Docker, Kubernetes, or OpenShift.
• ML Model Deployment: Familiarity with TensorFlow Serving, MLflow, or Dataiku Model API.
• Data Engineering: Experience with Spark, Databricks, Kafka, or Snowflake.
• ITIL/DevOps Certifications: ITIL Foundation, AWS ML certifications; Dataiku certification

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Production

• Industries

  Automation Machinery Manufacturing

Referrals increase your chances of interviewing at Net2Source Inc. by 2x

Sign in to set job alerts for “Operations Support Engineer” roles.

Project Environmental Geologist/Scientist/Engineer

Pottstown, PA $88,000.00-$141,000.00 2 weeks ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.