Operations Engineer Jobs
Operations Engineer jobs are open across manufacturing, technology, energy, and logistics, from entry-level to senior and principal roles, with specializations in process optimization, reliability engineering, and systems operations. Find a role that fits from the openings below and apply directly.
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Introduction:
We are seeking a Machine Learning Operations (MLOps) Engineer to 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
- Apache Spark / PySpark
- AWS SageMaker (Databricks, Azure ML, or Vertex AI experience is a plus)
- Kubernetes
- CI/CD pipelines
- 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
At BDIPlus, 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.
- Visa sponsorship.
- A culture that encourages creativity, ownership, collaboration, and continuous innovation.
Introduction:
We are seeking a Machine Learning Operations (MLOps) Engineer to 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
- Apache Spark / PySpark
- AWS SageMaker (Databricks, Azure ML, or Vertex AI experience is a plus)
- Kubernetes
- CI/CD pipelines
- 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
At BDIPlus, 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.
- Visa sponsorship.
- A culture that encourages creativity, ownership, collaboration, and continuous innovation.
Operations Engineer Jobs by Experience Level
Top Cities Hiring Operations Engineers
Explore operations engineer openings in the cities hiring most right now.
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Find Operations Engineer JobsOperations Engineer Job Market
Who's Hiring
- Amazon91
- CVS Health59
- SpaceX23
- Lockheed Martin23
- Northrop Grumman21
Top Industries Hiring
- Technology & Software118
- Retail38
- E-Commerce & Online Marketplaces37
- Electronics & Hardware29
- Insurance25
What Employers Look For
The qualifications that appear most often in operations engineer jobs.
- Bachelor's degree in industrial, mechanical, electrical, or systems engineering or a related field
- Experience with process improvement methodologies such as Lean, Six Sigma, or Kaizen
- Proficiency in data analysis tools including SQL, Python, Excel, or Tableau
- Familiarity with SCADA, PLC systems, or operations management software
- Strong root cause analysis and corrective action documentation skills
- Ability to read and interpret technical drawings, schematics, or system architecture diagrams
Tips for Your Operations Engineer Job Search
Tailor your resume to the environment
Operations engineer roles vary sharply between manufacturing floors, cloud infrastructure teams, and energy facilities. Adjust your resume language to match each environment, using the exact tooling and process terminology the job listing uses, not a generic operations template.
Quantify process improvements you've driven
Hiring managers in this role want to see numbers behind your work. Replace phrases like 'improved efficiency' with the actual reduction in downtime, cycle time, or defect rate you achieved. That specificity is what separates screened-out resumes from callbacks.
Apply early to roles that fit
Migrate Mate lists operations engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter for the right seniority signal
Job titles for this role are inconsistently used across industries. A 'senior operations engineer' at a startup may expect the same scope as a 'principal' at a large enterprise. Read the responsibilities section, not just the title, before deciding whether to apply.
Prepare a structured troubleshooting walkthrough
Interviewers consistently ask candidates to walk through a real failure they diagnosed and resolved. Prepare two or three examples that follow a clear structure: what failed, how you isolated the cause, what you changed, and what the outcome was. Vague stories get filtered out quickly.
Negotiate using verified scope, not comp data
When countering an offer, anchor your case on the documented scope of the role, the systems you'll own, and the complexity of the environment. Compensation discussions tied to concrete responsibilities land better than market comparison arguments with this hiring audience.
Operations Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most operations engineers?
The companies hiring the most operations engineers right now include Amazon, CVS Health, and SpaceX, with the largest share of openings in California, Texas, and Virginia, based on current listings on Migrate Mate as of August 2026. Demand is consistently strong in manufacturing, energy, and large-scale technology operations.
How many operations engineer jobs are remote?
About 52% of operations engineer openings are fully remote or hybrid as of August 2026, though this varies considerably by specialization. Roles focused on software systems operations, reliability engineering, and data pipeline management tend to offer the most remote flexibility, while plant-based and facilities-heavy roles are almost entirely on-site.
How do you become an operations engineer?
Start with a bachelor's degree in an engineering discipline such as industrial, mechanical, systems, or electrical engineering. Build hands-on experience through internships, co-ops, or entry-level roles focused on process analysis, equipment maintenance, or production support. Develop proficiency in data tools and a working knowledge of at least one process improvement framework. Certifications in Six Sigma or reliability engineering strengthen your profile for more specialized positions.
Can you get hired as an operations engineer with little experience?
Yes, entry-level operations engineer roles exist specifically for candidates early in their careers, particularly in manufacturing, logistics, and tech companies with structured rotation programs. Focus your applications on roles that list 'entry-level' or 'associate' in the title, highlight any project work where you analyzed a process or solved a production problem, and be ready to demonstrate analytical thinking in technical screens even without years of direct experience.
What does the operations engineer interview process look like?
Most operations engineer interviews run through an initial recruiter screen, a technical phone interview focused on your process knowledge and analytical methods, and a final round that typically includes a case study or take-home problem. On-site or panel interviews often involve a walkthrough of a real project you led, questions about how you've handled system failures, and a discussion of how you've used data to drive a decision.
Where can I find and apply to operations engineer jobs?
You can find and apply to operations engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your background, experience level, and preferred location, then apply directly to each one that fits.
See All 1,373+ Operations Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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