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Machine Learning Operations Jobs in New York, NY

Strivector Corp

Machine Learning

Manhattan, NY · On-site

They are seeking a Machine Learning professional capable of tackling research problems with commercial applications, applying technical expertise to real-world financial and operational challenges.

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All JobsMachine Learning Operations JobsMachine Learning Operations Jobs in New York, NY

Machine Learning Operations information

See New York, NY salary details

$23

$43

$67

How much do machine learning operations jobs pay per hour?

As of Aug 9, 2026, the average hourly pay for machine learning operations in New York, NY is $43.64, according to ZipRecruiter salary data. Most workers in this role earn between $36.54 and $46.30 per hour, depending on experience, location, and employer.

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.

What is the difference between Machine Learning Operations vs Data Scientist?

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks above average compared to other tech roles.
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in New York, NY as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution, with an average salary of $90,776 per year, or $43.6 per hour.

Machine Learning Operations Engineer

Valid8 Financial, Inc.

Manhattan, NY • On-site

$120 - $170/hr

Other

Medical, PTO

Posted 4 days ago

Job description

We are seeking aMachine Learning Operations (MLOps) Engineerto join our team. The MLOps Engineer will be responsible for building and maintaining the infrastructure that enables reliable deployment, monitoring, governance, and continuous improvement of production machine learning systems across enterprise client environments.

What You'll Do:
  • Design, build, and maintain scalable machine learning deployment pipelines.
  • Develop standardized model registries, artifact repositories, data versioning, and reproducible ML environments.
  • Build automated evaluation pipelines for production machine learning models.
  • Implement automated data quality monitoring including profiling, anomaly detection, validation, quarantine, and alerting.
  • Develop automated retraining workflows, promotion gates, rollback capabilities, and audit trails.
  • Monitor production environments for model drift, latency, prediction quality, infrastructure performance, and operational costs.
  • Troubleshoot production machine learning issues and lead incident response activities.
  • Build CI/CD pipelines supporting enterprise AI applications.
  • Collaborate closely with Data Scientists and client engineering teams to deploy and maintain AI solutions.
  • Ensure governance, security, lineage, reproducibility, and audit readiness across machine learning platforms.
Who You Are:
  • Passionate about building reliable AI infrastructure at enterprise scale.
  • Experienced deploying and maintaining production machine learning systems.
  • Strong analytical and troubleshooting skills.
  • Fast learner with attention to detail.
  • Excellent communication and collaboration skills.
  • Comfortable working with both software engineering and data science teams.

Education:Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related technical field.

Related Work Experience:3+ years supporting production machine learning platforms or cloud infrastructure.

Technical Skills:
  • Advanced SQL
  • Python
  • AWS SageMaker (Databricks, Azure ML, or Vertex AI experience is a plus)
  • Infrastructure as Code (Terraform, CloudFormation, or similar)
  • Model monitoring and ML observability tools
  • Data validation and automated testing frameworks
  • Statistics related to monitoring, model drift, and performance evaluation
  • Git and modern DevOps practices
Our Purpose and Culture

AtBDIPlus, we empower organizations to unlock the full potential of their data through AI, advanced analytics, and intelligent enterprise platforms. We partner with Fortune 500 organizations to build scalable data, AI, and machine learning solutions that solve complex business challenges and drive measurable business outcomes.

Innovation is at the core of everything we do. From modern data engineering and AI-powered products to cloud-native architectures and enterprise automation, our teams work on cutting-edge technologies that transform how businesses operate. We foster a collaborative culture where curiosity is encouraged, ideas are valued, and every employee has the opportunity to make a meaningful impact.

Working at BDIPlus offers:
  • The opportunity to work on enterprise-scale AI, machine learning, and data platform initiatives.
  • A diverse, collaborative, and highly innovative team.
  • Exposure to modern cloud technologies and cutting-edge AI platforms.
  • Continuous learning and professional development opportunities.
  • Full health and commuter benefits.
  • Competitive salary and annual bonus.
  • Standard paid time off, sick leave, and company holidays.
  • A culture that encourages creativity, ownership, collaboration, and continuous innovation.
Are you authorized to work in the United States? Are you authorized to work in the United States?

Will you now or in the future require sponsorship for employment visa status (e.g. H-1B status)? Will you now or in the future require sponsorship for employment visa status (e.g. H-1B status)?

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