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Machine Learning Infrastructure Engineer Jobs in New York

Optiver

Machine Learning Research Engineer

New York, NY

$224.30K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal ... Learning infrastructure, training, and inference challenges to advance our futures trading ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Virtu Financial

Machine Learning Engineer

New York, NY

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Atrium

Contract Machine Learning Engineer

Manhattan, NY · On-site

$75 - $110/hr

The team is building modern cloud-native infrastructure and advanced ML systems to support high-impact business initiatives, and they are looking to add a Contract Machine Learning Engineer. This is ...

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$200K/yr

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal ... Learning infrastructure, training, and inference challenges to advance our futures trading ...

Spotify

Machine Learning Engineer

New York, NY · On-site +1

$170K - $212K/yr

Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures. * Work with Data and ML Engineers to support transitioning ...

Spotify

Machine Learning Engineer

New York, NY · On-site +1

$170K - $212K/yr

Influence the technical design, architecture, and infrastructure decisions to support new and diverse machine learning architectures. * Work with Data and ML Engineers to support transitioning ...

Treeswift Inc

Machine Learning Engineer

New York, NY · On-site

... infrastructure. Our machine learning model development focuses on two primary areas: (a) LiDAR ... Strong programming skills in Python * Expertise in deep learning libraries such as PyTorch ...

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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 30, 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.
Senior Machine Learning Engineer, Public Sector

Senior Machine Learning Engineer, Public Sector

Scale AI

Manhattan, NY • On-site

Full-time

Posted 28 days ago

Job description

Job Summary:
Scale AI is committed to developing reliable AI systems for critical decisions, and they are seeking a Senior Machine Learning Engineer to enhance their products and customer experience. The role involves leveraging advanced AI techniques to deploy models in government systems and improve machine learning infrastructure.
Responsibilities:
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
• This role will require an active security clearance or the ability to obtain a security clearance
Qualifications:
Required:
• Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
• Solid background in algorithms, data structures, and object-oriented programming
• Strong programming skills in Python, experience in Tensorflow or PyTorch
• This role will require an active security clearance or the ability to obtain a security clearance
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
Preferred:
• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
• Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
• Experience with computer vision, generative AI models, large language models, or agentic systems
• Familiarity with ML evaluation frameworks and agentic model design
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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