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Machine Learning Platform Engineer Jobs (NOW HIRING)

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA

$112K - $154K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... Proven experience with distributed systems , cloud platforms (AWS preferred), containerization and ...

Veho

Senior Machine Learning Platform Engineer

Manhattan, NY · On-site

$115K - $158K/yr

Job Title Disabled veteran A veteran who served on active duty in the U.S. military and is entitled to disability compensation (or who but for the receipt of military retired pay would be entitled to ...

Veho

Senior Machine Learning Platform Engineer

Boston, MA

$113K - $155K/yr

Job Title Disabled veteran A veteran who served on active duty in the U.S. military and is entitled to disability compensation (or who but for the receipt of military retired pay would be entitled to ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

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How much do machine learning platform engineer jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for machine learning platform engineer in the United States is $63.95, according to ZipRecruiter salary data. Most workers in this role earn between $50.48 and $73.80 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Platform Engineer position, and why are they important?

A Machine Learning Platform Engineer should have strong programming skills (especially in Python or Java), knowledge of machine learning frameworks (like TensorFlow or PyTorch), and experience with cloud platforms and scalable infrastructure. Familiarity with containerization tools (such as Docker and Kubernetes), CI/CD systems, and relevant certifications in cloud or machine learning technologies is highly valued. Effective problem-solving, teamwork, and clear communication are crucial soft skills for collaborating across data science and engineering teams. These capabilities enable seamless creation and maintenance of robust, high-performance machine learning platforms for scalable model development and deployment.

What does a typical day look like for a Machine Learning Platform Engineer?

A typical day for a Machine Learning Platform Engineer involves designing, building, and maintaining the infrastructure that supports data science and machine learning workflows. You might spend your time developing new features for the platform, optimizing data pipelines, deploying models, and troubleshooting technical issues alongside data scientists and engineers. Collaboration is key—you’ll often work closely with cross-functional teams to understand requirements, ensure scalability, and improve the overall machine learning lifecycle. This role offers a challenging mix of software engineering and system design, so adaptability and a proactive mindset are important for success.

What is a Machine Learning Platform Engineer job?

A Machine Learning Platform Engineer designs, builds, and maintains the infrastructure that enables machine learning development and deployment at scale. They work on areas like data pipelines, model training workflows, monitoring, and cloud or on-premises platforms to ensure ML models run efficiently in production. Their role bridges software engineering and machine learning, focusing on automation, scalability, and reliability to support data scientists and ML engineers in delivering models faster and more effectively.

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Machine Learning Platform Engineer jobs near you

Senior Machine Learning Platform Engineer

FieldAI

Irvine, CA

$112K - $154K/yr

Full-time

Posted 5 days ago

Be an early applicant

Job description

FieldAI’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.
What You’ll Get To Do:
  • Design and manage scalable ML infrastructure with IaC tools (Terraform, CloudFormation).
  • Develop and optimize cloud-based pipelines for training, evaluation, and inference on multimodal datasets.
  • Build and operate data systems for large-scale video ingestion, indexing, and storage.
  • Maintain MLOps workflows for versioning, experiment tracking, reproducibility, and CI/CD.
  • Ensure reliability and observability with monitoring, logging, and alerting.
  • Collaborate with AI/ML Engineers to productionize workflows.
  • Optimize infrastructure for performance and cost across cloud and edge.
  • Enforce best practices in security, compliance, and maintainability.
  • Mentor and manage junior engineers, providing technical guidance and career development.
What You Have:
  • Bachelor’s/Master’s in Computer Science, Engineering, or related field (or equivalent experience).
  • 4+ years of industry experience in ML infrastructure or platform engineering.
  • Strong coding skills in Python/TypeScript and a strong foundation in software engineering best practices.
  • Proven experience with distributed systems, cloud platforms (AWS preferred), containerization and orchestration (Docker, Kubernetes/EKS, Ray), and serverless.
  • Hands-on experience building ML pipelines for distributed training and large-scale inference.
  • Strong knowledge of data management at scale, including preprocessing and retrieval of video/image datasets.
  • Proficiency with CI/CD pipelines, infrastructure-as-code (Terraform, CloudFormation), and automation.
  • Familiarity with MLOps tools (MLflow, Kubeflow, Airflow).
  • Experience with system monitoring and observability in production.
The Extras That Set You Apart:
  • Experience with vector databases (OpenSearch, Pinecone, Weaviate) for indexing and retrieval.
  • Familiarity with distributed training frameworks (Horovod, DDP/FSDP, DeepSpeed, Ray).
  • Hands-on experience with GPU orchestration and auto-scaling (Karpenter, SageMaker, EKS).
  • Experience with agentic AI deployment workflows, orchestration frameworks, and retrieval-augmented generation.
  • Strong knowledge of security and compliance in ML and cloud environments.
Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.

Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.

Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.

Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.

We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.