Machine Learning Operations Lead

3i People

Atlanta (GA)

Hybrid

USD 70,000 - 75,000

Full time

14 days+

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Benefits offered by this job

Medical insurance

Vision insurance

401(k)

Pension plan

Paid maternity leave

Paid paternity leave

Job summary

Une entreprise innovante recherche un Machine Learning Operations Lead pour rejoindre son équipe à Atlanta. Le candidat s'occupera du déploiement et de la gestion des modèles ML, en s'assurant de l'intégration fluide de ces solutions dans les produits. Des compétences en leadership, collaboration et automatisation sont essentielles pour réussir dans ce rôle permanent et hybride.

Qualifications

Expérience dans la mise en œuvre et la gestion d'outils de ML Ops.
Maitrise des concepts de déploiement et surveillance de modèles.
Capacité à collaborer avec les équipes IT et DevOps.

Responsibilities

Diriger le déploiement des modèles ML en production.
Gérer l'infrastructure et collaborer avec les équipes IT.
Développer des scripts d'automatisation pour le déploiement des modèles.

Skills

Collaboration

Leadership

Automatisation

Surveillance des modèles

Education

Diplôme en informatique ou domaine connexe

Job description

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Direct message the job poster from 3i People

At 3i People, we’re more than a staffing agency, we are career accelerators! Partnered with cutting edge tech firms and innovative companies, we connect top-tier talent with their dream jobs. Our mission is to open doors for professionals like you to thriving workplaces where you can leave your mark. Here is one such permanent job opportunity for a Machine Learning Operations Lead with a Fortune 500 manufacturing organization headquartered in Atlanta, GA. Hybrid work arrangements.

As the ML Ops Lead, you will play a critical role in bridging the gap between data science and production. You will be responsible for implementing and managing the infrastructure, processes, and tools necessary to deploy, monitor, and maintain machine learning models in a production environment. You will work closely with data scientists, engineers, and other stakeholders to ensure the seamless integration of machine learning solutions into our products and services.

Key Responsibilities:

ML Model Deployment: Lead the deployment of machine learning models into production environments, ensuring they are scalable, reliable, and maintainable.

Infrastructure Management: Collaborate with the IT and DevOps teams to provision and manage the necessary infrastructure, including cloud resources, containers, and data pipelines, to support machine learning workloads.

Automation: Develop and maintain automation scripts and tools for model deployment, monitoring, and retraining, with a focus on efficiency and reproducibility.

Model Monitoring: Implement robust monitoring and alerting systems to track model performance, data drift, and anomalies, and take proactive steps to address issues as they arise.

Security and Compliance: Ensure that machine learning models and data pipelines adhere to security and compliance standards, and work closely with security teams to address any vulnerabilities or risks.

Collaboration: Collaborate with data scientists and engineers to understand model requirements, and work together to optimize models for deployment.

Documentation: Maintain clear and comprehensive documentation of ML Ops processes, procedures, and configurations.

Continuous Improvement: Stay up-to-date with industry best practices and emerging technologies in ML Ops, and proactively identify opportunities to enhance the ML Ops workflow.

Team Leadership: Mentor and guide junior ML Ops engineers and contribute to their skill development.

Seniority level