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Machine Learning Infrastructure Engineer Jobs in New York

Tagup

Machine Learning Engineer

Manhattan, NY · On-site

We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next ... improve ML infrastructure and workflows. • Collaborate with customers to identify new data ...

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

They are seeking Machine Learning Engineers to build a platform for training, evaluating, and ... infrastructure for frontier model interpretability, training, and inference. • Integrate new ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical ... Experience building and maintaining training and inference infrastructure, with an understanding of ...

Jane Street

Machine Learning Engineer

New York, NY

We are looking for an engineer with robust experience in machine learning and strong mathematical ... Experience building and maintaining training and inference infrastructure, with an understanding of ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ

$127.90K - $168.60K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration ... Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance.

Hang

Machine Learning Engineer

New York, NY · On-site +1

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

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Machine Learning Infrastructure Engineer information

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$50.9K

$139K

$199.1K

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

As of May 31, 2026, the average yearly pay for machine learning infrastructure engineer in New York is $139,015.00, according to ZipRecruiter salary data. Most workers in this role earn between $117,600.00 and $154,300.00 per year, depending on experience, location, and employer.

What is a Machine Learning Infrastructure Engineer job?

A Machine Learning Infrastructure Engineer designs, builds, and maintains the systems that support the development and deployment of machine learning models. This includes managing data pipelines, optimizing model training and inference, and ensuring scalability and reliability in production environments. They work closely with data scientists, ML engineers, and DevOps teams to create efficient workflows and infrastructure. Key technologies often include cloud platforms, containerization, orchestration tools, and distributed computing frameworks.

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

To thrive as a Machine Learning Infrastructure Engineer, you need a strong background in computer science, cloud computing, distributed systems, and experience with machine learning frameworks, often supported by a degree in a related field. Familiarity with tools such as Docker, Kubernetes, Terraform, as well as cloud platforms like AWS, GCP, or Azure, and certifications in cloud or DevOps technologies are highly valued. Strong problem-solving abilities, effective communication, and collaboration skills help engineers work seamlessly with data scientists and cross-functional teams. These skills are essential to design, implement, and maintain robust, scalable infrastructure that enables efficient machine learning development and deployment.

What are some common challenges faced by Machine Learning Infrastructure Engineers, and how can these be addressed on the job?

Machine Learning Infrastructure Engineers often face challenges such as ensuring infrastructure scalability, managing resource allocation, and maintaining system reliability while supporting rapid experimentation by data science teams. Balancing the needs for flexibility in research environments with production-grade stability requires a deep understanding of both engineering best practices and the unique requirements of machine learning workflows. Collaboration with data scientists, clear communication about infrastructure capabilities, and staying current with fast-evolving technologies are key strategies for success. Most companies encourage ongoing learning and provide opportunities to contribute to architecture decisions, which makes this a rewarding environment for problem-solvers and innovators.
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Machine Learning Infrastructure Engineer jobs near you
Infographic showing various Machine Learning Infrastructure Engineer job openings in New York as of May 2026, with employment types broken down into 88% Full Time, 6% Part Time, 5% Contract, and 1% Summer. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $139,015 per year, or $66.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Tagup

Manhattan, NY • On-site

Full-time

Posted 13 days ago

Job description

Job Summary:
Tagup is a defense technology company founded at MIT that is delivering logistics decision advantage with next-generation AI. We are seeking a Machine Learning Engineer to join our Salt Lake City team and help shape the next generation of AI-driven defense and aviation systems by designing, deploying, and scaling AI solutions that support mission-critical operations.
Responsibilities:
• Develop, train, and optimize ML models for large-scale applications.
• Build pipelines for data ingestion and model deployment.
• Work with engineers and subject-matter experts to refine solutions.
• Conduct testing and validation to ensure reliability.
• Co-author technical reports on data analysis and model performance.
• Continuously improve ML infrastructure and workflows.
• Collaborate with customers to identify new data sources and the industrial processes they will support; some customer travel may be required.
Qualifications:
Required:
• 4+ years of machine learning experience, with strong Python skills and proficiency in frameworks such as PyTorch or TensorFlow.
• Proven ability to deploy ML models into production and work with large, complex datasets.
• Hands-on experience with MLOps tools and practices, including Kubernetes, MLflow, and CI/CD pipelines.
• Experience building and managing cloud infrastructure as code (AWS, Azure, or GCP) with tools such as Terraform or Ansible.
• Familiarity with datastores (MySQL, Postgres, or MongoDB) and prior exposure to aviation, defense, or other safety-critical environments is a plus.
Company:
Tagup provides asset management decision support, lowering the cost of in-service failures, business interruption, and equipment breakdown. Founded in 2015, the company is headquartered in Somerville, USA, with a team of 11-50 employees. The company is currently Early Stage.

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