AI ML Operations Engineer
Job
OOG Occidental Oil & Gas Corp
Houston, TX (In Person)
Full-Time
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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 looking for an experienced and innovative individual contributor to fill the position of AI Machine Learning Operations Engineer within our AI Center of Excellence group based in Houston, TX. The incumbent will research, build, and design artificial intelligence systems to automate predictive models, and design machine learning systems, models and schemes. Essential Job Responsibilities Designs production-grade ML systems end-to-end (data → training → deployment → monitoring) with experience Owns production systems (debugging, incident response, reliability, SLAs, cost awareness) Strong data engineering fundamentals (pipeline reliability, data quality, versioning, and data) Builds reusable platform patterns that reduce duplication and enable teams to ship faster and more safely Navigates cloud architecture complexity (AWS/Databricks/IaC) with a bias toward simplicity and maintainability Works effectively across teams (data science, engineering, platform), can lead training, can influence adoption Understanding of emerging agentic and LLM assisted development patterns Qualifications Bachelor's degree in computer science, mathematics, physics, engineering or related field required Master's degree is highly preferred. Equivalent combination of advanced education and relevant experience will be considered. A minimum of 3 years of experience and deep knowledge in orchestration methods and tools to optimally use computational infrastructure, and machine learning methods and algorithms Strong Python or R programming skills required Knowledge of Linux environment required Strong knowledge of Microsoft products (Excel, Project, PowerPoint, Word, Power BI). Experience developing, architecting, and running ML or deep learning workload in the Cloud. Ability to express the intuition behind basic ML algorithms Experience performing basic hyper parameter optimization Ability to follow model training, deployment, and operational best practices Experience with Docker for containerization and Kubernetes for orchestration Knowledge of Terraform and Ansible for automating infrastructure management Knowledge of YAML for automating model and application code deployment Understanding of data engineering principles and databases (relational, NoSQL)
Additional Desired Qualifications:
Certified in Amazon Web services (AWS) cloud provider is highly preferred. Ideally AWS certified in Machine Learning Specialty Occidental does not offer sponsorship of employment-based nonimmigrant visa petitions for this role. 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.
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