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Gcp Machine Learning Engineer Jobs (NOW HIRING)

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

We are seeking a Machine Learning Engineer with a passion for building mission-critical ... Familiarity working in cloud environments (AWS, Azure, or GCP) and modern development practices ...

Kindredventures

Machine Learning Engineer

Seattle, WA · On-site

$125 - $150/hr

The role We're adding an Machine Learning Engineer to our team to help us build and scale our core ... The tech stack Our backend tech stack is based on Python, GCP, Go, protobufs, BigQuery and MySQL.

New

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for ... AWS, GCP, Azure). • Excellent communication and collaboration skills, capable of working ...

Spear AI

Machine Learning Engineer

They are seeking a skilled Machine Learning Engineer to build and deploy production ML systems for ... AWS, Azure, GCP) • Proficiency with MLOps practices including experiment tracking, model ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI ... AWS, GCP, Azure). • Excellent communication and collaboration skills, capable of working ...

FloVision Solutions

Machine Learning Engineer

POSITION OVERVIEW As a Machine Learning Engineer at FloVision, you will design, develop, and ... At least two years of experience working with a major cloud platform such as AWS, GCP, or Azure

Grid

Machine Learning Engineer

Seattle, WA

$120K - $140K/yr

The role We're adding an Machine Learning Engineer to our team to help us build and scale our core ... The tech stack Our backend tech stack is based on Python, GCP, Go, protobufs, BigQuery and MySQL.

FloVision Solutions

Machine Learning Engineer

OR · On-site +1

POSITION OVERVIEW As a Machine Learning Engineer at FloVision, you will design, develop, and ... At least two years of experience working with a major cloud platform such as AWS, GCP, or Azure

Grid

Machine Learning Engineer

Seattle, WA

$120K - $140K/yr

The role We're adding an Machine Learning Engineer to our team to help us build and scale our core ... The tech stack Our backend tech stack is based on Python, GCP, Go, protobufs, BigQuery and MySQL.

Talanto

$200 - $250/hr

Python PyTorch TensorFlow AWS GCP Important: if an employer asks you to log into their system via ... Senior Machine Learning Engineer * Location: Remote * Employment Type: Full-time Compensation:

FastTek

Machine Learning Engineer

Dearborn, MI · On-site

Python, Machine Learning, Data Science, GCP, BigQuery Experience Requirements: * Engineer Level 3 * 6+ years of IT experience * 4+ years of development experience * Experience with 2 programming ...

PhysicsX

Machine Learning Engineer

New York, NY · On-site

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ... Cloud platforms (e.g., AWS, Azure, GCP) and HP computing * Containerization and orchestration ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ... Cloud platforms (e.g., AWS, Azure, GCP) and HP computing * Containerization and orchestration ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ... Cloud platforms (e.g., AWS, Azure, GCP) and HP computing * Containerization and orchestration ...

HeadHR

NY · On-site

$60 - $80/hr

... GCP), * rozumiesz architekturę rozwiązań Machine Learning oraz LLM i potrafisz je wdrażać w środowisku produkcyjnym, * znasz zagadnienia związane z MLOps / DevOps, * swobodnie poruszasz się w ...

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Gcp Machine Learning Engineer information

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How much do gcp machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for gcp machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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Infographic showing various Gcp Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

Chantilly, VA • On-site, Remote

NT Concepts
IT Services • 51 - 200 employees
Learn more about NT Conceptsexternal

Full-time

Posted 4 days ago

Job description

 

We are seeking a Machine Learning Engineer with a passion for building mission-critical capabilities to join our talent network. Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, explore What's Next with us.

Mission Focus: Our machine learning teams bridge the gap between cutting-edge AI research and operational government missions. We are looking for engineers who can take machine learning and Computer Vision (CV) solutions from early research and prototyping all the way into stable, scalable production environments.

 

In this role, you will help design, build, and deploy automated ML workflows that directly support national security analysts and operators. We embrace modern agile practices, a DataOps/DevSecOps/MLOps ethos to "automate-first," and modern cloud-native architectures.

Clearance: Active TS/SCI required (CI Polygraph preferred or must be eligible to obtain)

Location/Flexibility: Vienna, VA / Chantilly, VA (Hybrid / Flexible Remote options available)

Responsibilities 

  • Prototype to Production: Support the full machine learning lifecycle, taking computer vision models from experimentation and notebooks into containerized, high-throughput production microservices.
  • Mission Alignment: Work closely with mission partners, domain experts, and technical teams to understand real-world operational challenges and translate them into practical ML requirements.
  • MLOps & Pipeline Automation: Build, maintain, and optimize robust pipelines for data preparation, model training, validation, versioning, deployment, and monitoring using modern tools (such as MLflow, Kubeflow, and GitLab CI/CD).
  • Model Development & Tuning: Train, fine-tune, and evaluate deep learning algorithms for computer vision tasks (e.g., object detection, classification, segmentation, tracking).
  • System Integration: Collaborate with cross-functional software engineers and cloud architects to integrate ML models cleanly into larger enterprise systems and secure cloud infrastructures.
  • Optimization & Governance: Optimize inference performance, apply secure coding practices, and monitor models for drift and reliability once deployed. 

 Qualifications

  • Clearance: Active TS/SCI clearance.
  • Hands-On Experience: Demonstrated professional experience developing, testing, and deploying machine learning models into real-world or production environments.
  • Deep Learning & CV: Strong programming skills in Python and hands-on experience with deep learning frameworks (primarily PyTorch, OpenCV, TensorFlow, or NumPy).
  • ML Lifecycle & MLOps: Practical familiarity with containerization (Docker, Kubernetes) and ML lifecycle/pipeline platforms (e.g., MLflow, Kubeflow, AWS SageMaker).
  • Cloud & DevOps Foundations: Familiarity working in cloud environments (AWS, Azure, or GCP) and modern development practices (Git, CI/CD pipelines, Agile methodologies).
  • Customer & Mission Mindset: Ability to understand the end-user's mission objectives, iterate based on user feedback, and clearly communicate technical approaches. 

Preferred / Desired Skills:

  • Experience working within secure, air-gapped, or classified cloud environments (e.g., AWS GovCloud / C2S).
  • Experience with synthetic data generation techniques or multi-modal models.
  • Exposure to Large Language Models (LLMs) or generative AI workflows.
  • Familiarity with distributed model training and GPU resource management. 

Physical Requirements

  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 10-15 pounds at times.

#JT

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