Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Advisor IT Systems - AI/ML Ops
Houston, Texas
Open 6 months, first seen by us 192 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDesign, build, and maintain MLOps pipelines for training, deployment, monitoring, and retraining on AWS
Operationalize ML models for upstream use cases like production optimization and drilling analytics
Implement CI/CD, model versioning, experiment tracking, and performance monitoring
Move models from development to production with data scientists and data engineers
Ensure reliability, observability, governance, and compliance of ML systems
From the employer’s posting
Design, build, and maintain MLOps pipelines and platforms for model training, deployment, monitoring, and retraining using AWS.
Operationalize ML models for upstream use cases (e.g., production optimization, subsurface modeling, drilling analytics).
Implement CI/CD, model versioning, experiment tracking, and performance monitoring.
Collaborate with data scientists, data engineers, and domain experts to move models from development to production.
Ensure reliability, observability, governance, and compliance of ML systems.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience in data engineering, software engineering, MLOps, or AI Ops.
- Strong proficiency in Python for production‑grade ML workflows.
- Experience deploying and supporting ML models in production environments.
- Familiarity with CI/CD tools, Docker, and Kubernetes.
- Understanding of ML lifecycle management, model monitoring, and data drift.
Preferred experience
- Experience supporting analytics or ML solutions in upstream Oil & Gas or energy.
- Knowledge of time‑series, forecasting, or physics‑informed ML workloads.
- Experience with infrastructure‑as‑code (Terraform, CloudFormation).
Qualification wording
5+ years of experience in data engineering, software engineering, MLOps, or AI Ops.
Strong proficiency in Python for production‑grade ML workflows.
Experience deploying and supporting ML models in production environments.
Familiarity with CI/CD tools, Docker, and Kubernetes.
Understanding of ML lifecycle management, model monitoring, and data drift.
Experience supporting analytics or ML solutions in upstream Oil & Gas or energy.
Knowledge of time‑series, forecasting, or physics‑informed ML workloads.
Experience with infrastructure‑as‑code (Terraform, CloudFormation).
Posting record
Report an errorOpen 6 monthsWe first saw this posting 192 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 27, 2026192 days ago
- Recorded sightings
- 174
- Last seen by us
- Nov 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 192
Up longer than most. Similar jobs usually come down between day 6 and day 70.
From 4,442 similar postings that came down. Coming down is not always a hire.
Occidental Petroleum is hiring
4 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Its jobs tend to stay up a long time
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- Docker
- Kubernetes
- S3
- SageMaker
- Terraform
Where the posting names them
- Good grasp of software architecture principles and systems design - Strong proficiency in Python for production‑grade ML workflows. - Hands‑on experience with AWS (e.g., S3, EC2, EKS/ECS, SageMaker, Lambda, CloudWatch).
Key Responsibilities - Design, build, and maintain MLOps pipelines and platforms for model training, deployment, monitoring, and retraining using AWS. - Operationalize ML models for upstream use cases (e.g., production optimization, subsurface modeling, drilling analytics).
- Strong proficiency in Python for production‑grade ML workflows. - Hands‑on experience with AWS (e.g., S3, EC2, EKS/ECS, SageMaker, Lambda, CloudWatch). - Experience deploying and supporting ML models in production environments.
- Experience deploying and supporting ML models in production environments. - Familiarity with CI/CD tools, Docker, and Kubernetes. - Understanding of ML lifecycle management, model monitoring, and data drift.
- Knowledge of time‑series, forecasting, or physics‑informed ML workloads. - Experience with infrastructure‑as‑code (Terraform, CloudFormation). Recruitment Fraud It has come to our attention various individuals and/or organizations are contacting people falsely pretending to recruit on behalf of Oxy. Please be aware that these recruiting scams and communications do not originate nor are they associated with our recruitment process. All Oxy job postings and offers will require a completed application through our company website. Oxy does not charge a fee at any stage of the recruiting process. We will never: • Ask you to pay for applications, interviews, meetings, processing, training or for any other fees • Use recruiting or placement agencies that charge candidates an advance fee of any kind or • Request personal information such as passport and bank account details at an early stage of our recruitment process. We recommend against responding to unsolicited business propositions or offers from people you don't know. Do not disclose your personal or financial details. If you believe you have been the victim of a recruiting scam, please contact your local police department.
Your next step
Complete your application on oxy.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Applying through Workday
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- Your application status lives in that employer’s Candidate Home, under the same sign-in.
Already applied? Track this application
About Occidental Petroleum
- People
- About 9,533 in 2024.Benefit plan filings (Form 5500)
- Company
- Listed as OXY.
- H-1B visas
- 8 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
Oxy produces, markets and transports oil and natural gas to maximize value and provide resources fundamental to life. The company leverages its global leadership in carbon management to advance lower-carbon technologies and products. Headquartered in Houston, Oxy primarily operates in the United States, Middle East and North Africa. To learn more, visit Oxy
Oxy strives to attract and retain talented employees by investing in their professional development and providing rewarding opportunities for personal growth. Our goal is to meet the highest employer standards by ensuring the health and safety of our employees, protecting the environment and positively impacting our communities where we do business.
We are seeking a mid‑career MLOps / AI Ops Engineer to support the deployment, monitoring, and lifecycle management of machine learning and advanced analytics solutions across upstream Oil & Gas operations. This role bridges data science, cloud engineering, and operations to ensure reliable, scalable, and secure AI systems in production.
Key Responsibilities
Design, build, and maintain MLOps pipelines and platforms for model training, deployment, monitoring, and retraining using AWS.
Operationalize ML models for upstream use cases (e.g., production optimization, subsurface modeling, drilling analytics).
Implement CI/CD, model versioning, experiment tracking, and performance monitoring.
Collaborate with data scientists, data engineers, and domain experts to move models from development to production.
Ensure reliability, observability, governance, and compliance of ML systems.
Troubleshoot production issues related to data, models, and infrastructure.
Required Qualifications
5+ years of experience in data engineering, software engineering, MLOps, or AI Ops.
Good grasp of software architecture principles and systems design
Strong proficiency in Python for production‑grade ML workflows.
Hands‑on experience with AWS (e.g., S3, EC2, EKS/ECS, SageMaker, Lambda, CloudWatch).
Experience deploying and supporting ML models in production environments.
Familiarity with CI/CD tools, Docker, and Kubernetes.
Understanding of ML lifecycle management, model monitoring, and data drift.
Preferred Qualifications
Experience supporting analytics or ML solutions in upstream Oil & Gas or energy.
Knowledge of time‑series, forecasting, or physics‑informed ML workloads.
Experience with infrastructure‑as‑code (Terraform, CloudFormation).
Recruitment Fraud
It has come to our attention various individuals and/or organizations are contacting people falsely pretending to recruit on behalf of Oxy. Please be aware that these recruiting scams and communications do not originate nor are they associated with our recruitment process. All Oxy job postings and offers will require a completed application through our company website.
Oxy does not charge a fee at any stage of the recruiting process. We will never:
• Ask you to pay for applications, interviews, meetings, processing, training or for any other fees
• Use recruiting or placement agencies that charge candidates an advance fee of any kind or
• Request personal information such as passport and bank account details at an early stage of our recruitment process.
We recommend against responding to unsolicited business propositions or offers from people you don't know. Do not disclose your personal or financial details. If you believe you have been the victim of a recruiting scam, please contact your local police department.
All qualified applicants will receive consideration for employment without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
Source details
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Houston, Texas
Working pattern and location restrictions need checking in the full posting.
- Work authorization
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