Technology

AI/ML Platform Engineer

MetaSense, Inc.Linthicum Heights, MD🇺🇸United StatesPosted Oct 19, 2026

Quick Overview

Seniority

Mid Senior

Work mode

On Site

Location

Linthicum Heights, MD, United States

Posted

23 hours ago

DockerAWSMLflowNLPScikit-learnAirflowAnsibleApacheAzureComputer VisionDatadogDeep LearningGenerative AIGitHub ActionsGitLab CIGoogle CloudGrafanaJenkinsKubernetesPrometheusPyTorchPythonTensorFlowTerraform

Job Description

Title: AI/ML Platform Engineer

Location: Linthicum Heights, MD (5 days onsite)

Duration: Long Term (12+ months)

Interview Mode: Video + Onsite

Position Overview:

The AI/ML Platform Engineer will develop, maintain, and optimize infrastructure, tools, and automated workflows supporting the shared enterprise AI/ML platform. The role focuses on ML pipeline automation, CI/CD, model deployment, monitoring, cloud cost optimization, and developer enablement.

Key Requirements:

5+ years of experience in software engineering, data engineering, or ML engineering, including 2+ years working with production ML systems.
Bachelor's degree in Computer Science, Engineering, or a related technical field; master's degree or PhD preferred.
Strong proficiency in Python and production-quality code development.
Understanding of ML and deep learning fundamentals, including model training, evaluation, feature engineering, versioning, and deployment.
Experience with PyTorch, TensorFlow, or scikit-learn.
Experience with Apache Airflow, Kubeflow Pipelines, Prefect, or equivalent orchestration tools.
Familiarity with AWS, Azure, or Google Cloud Platform and managed AI/ML services.
Experience with Docker, basic Kubernetes operations, and CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins.
Experience building, deploying, monitoring, and troubleshooting ML pipelines and production workflows.
Experience monitoring model performance, data drift, pipeline health, and infrastructure utilization.
Strong analytical, debugging, communication, and collaboration skills.

Preferred Experience:

Prometheus, Grafana, or Datadog.
MLflow or Weights & Biases.
Terraform or Ansible.
Feature stores such as Feast or Tecton.
Internal developer tools, SDKs, and self-service platform capabilities.
NLP, computer vision, speech processing, reinforcement learning, or Generative AI.
Government, regulated, or large enterprise environments.