Machine Learning Engineer

ADT; Boca Raton (FL); À distance; USD 110 000 - 170 000; Plein temps

Avantages offerts par ce poste

Remote work

Résumé du poste

ADT is seeking a Machine Learning Engineer to design, build, and deploy production-grade ML models within its Data & AI organization. This role bridges data science research and software engineering, taking theoretical models and scaling them to run efficiently across ADT’s vast ecosystem—from high-throughput cloud architectures to edge devices and smart home IoT telemetry.

You will join cross-functional teams to embed ML capabilities into customer-facing ADT applications, ensuring robust

Qualifications

• Bachelor’s degree in CS/Math/related field or equivalent.
• 3+ years of professional software or ML engineering experience.
• Advanced Python and OO design skills.
• Deep experience with ML frameworks (PyTorch, TensorFlow, Scikit-Learn).
• Strong GCP knowledge: Vertex AI, BigQuery, GCS; data pipelines experience.
• Docker, Kubernetes, CI/CD, and MLOps practices.
• Ability to manage multiple priorities in a fast-paced environment.
• Excellent communication and teamwork.

Responsabilités

• Design, build and deploy production-grade ML models.
• Operationalize ML pipelines using Vertex AI Pipelines and Kubeflow/TFX.
• Optimize models for latency and edge deployments.
• Monitor performance and drift with Vertex AI Model Monitoring.
• Collaborate with data engineering and platform teams on feature stores and data warehouses.
• Embed ML capabilities into ADT apps via APIs and microservices.
• Maintain code quality with modular design, tests, and docs.

Connaissances

Python

PyTorch

TensorFlow

GCP Vertex AI

BigQuery

Kubernetes

SQL

MLOps

Formation

Bachelor’s degree in CS/related

Master’s preferred

Outils

Docker

Kubernetes

Vertex AI Pipelines

GCS

BigQuery

Dataflow

Description du poste

3021789

Summary

The Machine Learning Engineer will be responsible for designing, building, and deploying production-grade machine learning models and AI systems within ADT's Data & AI organization. This role bridges the gap between data science research and software engineering, taking theoretical models and scaling them to run efficiently across ADT’s vast ecosystem—from high-throughput cloud architectures to edge devices and smart home IoT telemetry.

Duties and Responsibilities

• Production Deployment & Scaling: Operationalize and scale machine learning models into production systems via GCP Vertex AI, ensuring low-latency execution and high availability.
• MLOps & Pipeline Automation: Design, implement, and maintain robust end-to-end ML pipelines for data preprocessing, continuous model training, and evaluation using Vertex AI Pipelines (Kubeflow/TFX) and GCP CI/CD toolchains.
• Model Optimization: Optimize ML algorithms, large language models (LLMs), and deep learning models for computational efficiency using GCP infrastructure (GPUs/TPUs) and edge‑computing constraints.
• Monitoring & Drift Detection: Build tracking and observability systems to monitor production model performance, logging, and data/concept drift leveraging Vertex AI Model Monitoring and Google Cloud Storage solutions.
• Infrastructure Collaboration: Partner with data engineering and platform teams to design, manage, and optimize scalable feature stores (Vertex AI Feature Store) and high‑dimensional analytical data warehouses (BigQuery).
• Cross-Functional Integration: Collaborate with software engineering and product development teams to embed ML capabilities into customer-facing ADT applications and core services via microservices/APIs.
• Code Quality & Best Practices: Champion rigorous software engineering principles within the data science organization, including modular code design, comprehensive testing (unit/integration), and technical documentation.
• Continuous Innovation: Stay current with the rapidly evolving ML engineering landscape, adopting cutting-edge tools, framework upgrades, and hardware accelerations to keep ADT competitive.

Minimum Qualifications

• Education: Bachelor’s degree (or equivalent experience) in Computer Science, Software Engineering, Data Science, Mathematics, or a highly quantitative field. (Master's degree preferred).
• Experience: 3+ years of professional software engineering or machine learning engineering experience, with a proven track record of deploying models to production environments.
• Technical Proficiency:
• Advanced, production-grade proficiency in programming languages like Python, with strong object-oriented design skills.
• Deep experience with core ML frameworks and libraries (e.g., PyTorch, TensorFlow, Scikit-Learn, XGBoost).
• Strong familiarity with Google Cloud Platform (GCP), specifically Vertex AI (Pipelines, Feature Store, Model Registry), BigQuery, and Google Cloud Storage (GCS).
• Solid experience constructing high-dimensional data pipelines using SQL, Spark on GCP, or Google Cloud Dataflow.
• Software Practices: Strong understanding of Docker, Kubernetes (Google Kubernetes Engine - GKE), MLOps, CI/CD toolchains, and Bitbucket.
• Ambiguity Management: Versatility to manage multiple technical priorities, apply structure to complex engineering challenges, and thrive in a fast-paced environment.

Required Licensing or Certifications

• Highly Preferred: Google Cloud Certified Professional Machine Learning Engineer or Professional Cloud Architect

Communication Skills

• Writing, Talking/Hearing on the phone (Continually=67-100% of workday)

Environment Requirements

• Remote/Home office (Continually=67-100% of the workday)

Travel

• Occasionally, less than 25%

In the event a position is commission-based, compensation is solely based on the individual’s sales volume. This applies only to commission roles.

Los Angeles Applicants: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

Philadelphia Applicants: Background checks will be conducted during the employment process. Any information will be reviewed through an individualized assessment in accordance with the Philadelphia Fair Criminal Record Screening Standards Ordinance.

ADT is an Equal Employment Opportunity (EEO) Employer. We celebrate diversity and are committed to building an inclusive team that represents a variety of backgrounds, perspectives, and skills. ADT strives to ensure every employee and applicant feels valued. Visit us at jobs.adt.com/diversity to learn more.