AI Platform / ML Engineer

Greymatter Innovationz; New York (NY); Sur place; USD 120 000 - 150 000; Plein temps

Avantages offerts par ce poste

Motivating Work Environment

Excellent Work Culture

Career development

Résumé du poste

Greymatter Innovationz in NYC is seeking an AI Platform / ML Engineer to build, operationalize, and scale ML solutions. You will develop reusable workflows, integrate data sources, and ensure reliable model deployment and lifecycle management across platforms like Dataiku and Databricks.

The role emphasizes MLOps, collaboration with data scientists and engineers, and delivering production-ready AI capabilities in a fast-paced, cross-functional team.

Qualifications

• 3–6 years of experience in MLOps, machine learning engineering, or AI model deployment.
• Hands-on experience with platforms like Dataiku or Databricks for building and managing ML workflows.
• Strong programming in Python, familiarity with SQL, and experience with containerization/CI-CD pipelines for AI models.
• Strong collaboration skills and ability to work in cross-functional teams.

Responsabilités

• Model Operationalization (MLOps): Build, test, and deploy AI and ML solutions into production environments using Dataiku, Databricks, or similar platforms.
• Workflow Development: Create reusable workflows and integrate ML pipelines with core data sources.
• Monitoring & Maintenance: Monitor model performance, drift, and production operations; support continuous improvement.
• Team Collaboration: Work with data scientists, data engineers, and business analysts to bridge experiments and enterprise apps.

Connaissances

MLOps

Python

SQL

CI/CD pipelines

Cross-functional collaboration

Outils

Dataiku

Databricks

Docker

Description du poste

Greymatter Innovationz helps you stay digitally relevant across domains, technologies, and skillsets, every day.

We are looking for:

AI Platform / ML Engineer

Location: NYC

Employment Type: Full-Time

About the Role

We are looking for an AI Platform / ML Engineer to develop, operationalize, and scale machine learning and AI solutions. You will be responsible for building reusable workflows, integrating diverse data sources, and ensuring reliable model deployment, monitoring, and lifecycle management across platforms like Dataiku and Databricks.

Key Responsibilities

• Model Operationalization (MLOps): Build, test, and deploy AI and machine learning solutions into production environments using Dataiku, Databricks, or similar MLOps platforms.
• Workflow Development: Create reusable workflows, streamline data preparation, and integrate machine learning pipelines with core data sources.
• Monitoring & Maintenance: Monitor model performance, track drift, and support continuous improvement, scaling, and production operations.
• Team Collaboration: Collaborate with data scientists, data engineers, and business analysts to bridge the gap between experimental models and robust enterprise applications.

Key Requirements & Skills

• Experience: 3–6 years of experience focusing on MLOps, machine learning engineering, or AI model deployment.
• Platform Expertise: Hands-on experience with platforms like Dataiku or Databricks for building and managing ML workflows.
• Technical Skills: Strong programming background in Python, familiarity with SQL, and experience with containerization/CI-CD pipelines for AI models.
• Collaboration: Strong communication skills with an ability to work collaboratively in fast-paced, cross-functional tech teams.

We offer:

• Motivating Work Environment.
• Excellent Work Culture.
• Help you to upgrade yourself to the next level.

And More!!!