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Machine Learning Infrastructure Engineer Jobs in Brooklyn, NY

Microsoft AI

Machine Learning

Manhattan, NY · On-site

... engineering experience with coding in languages including, but not limited to, C, C++, C#, Java ... creating infrastructure for AI-powered products). • OR Bachelor's Degree in Computer Science ...

Inizio Partners

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

As a GCP ML Engineer, you'll design, develop, and maintain machine learning pipelines and infrastructure on the Google Cloud Platform (GCP). You'll work closely with data scientists, engineers, and ...

CNN

Machine Learning Engineer I

Manhattan, NY · On-site

... serving infrastructure • Implement rigorous experimentation and A/B testing frameworks to ... machine learning systems in production environments • Strong Python programming skills and ...

Tennr

Staff Backend Software Engineer

Manhattan, NY · On-site

They are seeking a Senior Backend Engineer to architect and implement features across their backend services, with an emphasis on workflow automation and machine learning infrastructure.

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

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

Jane Street

Machine Learning Engineer

Manhattan, 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 ...

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All JobsMachine Learning Infrastructure Engineer JobsMachine Learning Infrastructure Engineer Jobs in Brooklyn, NY

Machine Learning Infrastructure Engineer information

See Brooklyn, NY salary details

$48.9K

$133.6K

$191.4K

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

As of Jun 17, 2026, the average yearly pay for machine learning infrastructure engineer in Brooklyn, NY is $133,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $148,300.00 per year, depending on experience, location, and employer.

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.

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 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 popular job titles related to Machine Learning Infrastructure Engineer jobs in Brooklyn, NY? For Machine Learning Infrastructure Engineer jobs in Brooklyn, NY, the most frequently searched job titles are:
What job categories do people searching Machine Learning Infrastructure Engineer jobs in Brooklyn, NY look for? The top searched job categories for Machine Learning Infrastructure Engineer jobs in Brooklyn, NY are:
Machine Learning Infrastructure Engineer jobs near you
Infographic showing various Machine Learning Infrastructure Engineer job openings in Brooklyn, NY as of June 2026, with employment types broken down into 80% Full Time, 11% Part Time, 4% Temporary, and 5% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $133,611 per year, or $64.2 per hour.

Machine Learning

Microsoft AI

Manhattan, NY • On-site

Full-time

Posted 5 days ago

Job description

Job Summary:
Microsoft AI is a part of Microsoft focused on pushing the boundaries of AI towards Humanist Superintelligence. The role involves creating LLM models for general purpose capabilities and products, developing new training methods, and collaborating with research and product teams.
Responsibilities:
• Own and pursue a research agenda to improve model capability and performance for agentive application.
• Collaborate closely with the other research and product teams, from pretraining to model hosting to unlock new model capabilities.
• Build robust evaluations for tracking modeling improvements.
• Design, implement, test, and debug code across our research stack.
Qualifications:
Required:
• Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python + OR equivalent experience.
• Demonstrated engineering experience or research experience (e.g. creating or leading the creation of a feature in a different company, complex graduate work, research papers, or other experience).
• Experience prompting, evaluating, and working with large language models.
• Experience writing production-quality Python code.
Preferred:
• Doctorate in Computer Science, Machine Learning, Human-Centered AI or related field AND 2+ year(s) experience (e.g., finetuning models with supervision or reinforcement learning, understanding and fixing data quality and curation, working with collaborators on creating new products).
• OR Master's Degree in Computer Science, Machine Learning, or related field AND 5+ years experience (e.g., managing structured and unstructured data, developing and debugging models, creating infrastructure for AI-powered products).
• OR Bachelor's Degree in Computer Science, Mathematics, Machine Learning, Physics, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying machine learning techniques and driving product direction).
Company:
Microsoft AI is a software development company. Founded in 2024, the company is headquartered in Redmond, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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