Machine Learning Engineer
At a glance
Mid-level Machine Learning Engineering role at Corning. Obispado.
Pay not stated Machine Learning Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and maintain ML workflows covering data intake, preparation, model training, checks, release, monitoring and retraining
- Work with data scientists and engineers to turn trial models into solutions ready for production
- Enable model use through APIs, batch processing or real-time services, applying MLOps for tracking, orchestration and CI/CD
- Resolve data, model, deployment and integration problems, while documenting technical decisions and reviewing code
What you bring
- A bachelor's degree in computer science, engineering or another listed technical discipline
- Up to two years of relevant experience, including hands-on academic, internship, personal or professional projects
- Strong Python skills and practical use of at least one ML library, such as scikit-learn, TensorFlow or PyTorch
- Advanced English for technical and business communication, plus the ability to explain your project work and results
Who this fits
This role suits an early-career engineer with practical machine learning work who can explain their contribution to a project. You need to work onsite in Monterrey at least two days each week and support plant-based projects when needed. The position offers hybrid flexibility.
From the employer
Are you ready to turn machine learning ideas into reliable solutions that improve how products are made?
What is your role?
As a Machine Learning Engineer, you will work within a collaborative technical team to build, deploy, monitor, and maintain machine learning solutions that create measurable business value. You will partner with data scientists, analytics leaders, IT, and manufacturing teams to move models from experimentation into scalable and reliable production environments. This role is based in Monterrey and requires regular onsite presence, with hybrid flexibility.
Major responsibilities and tasks of the position:
- Participate in the development and maintenance of end-to-end machine learning pipelines, including data ingestion, preprocessing, training, validation, deployment, monitoring, and retraining.
- Collaborate with data scientists and engineers to translate prototypes and experimental models into production-ready solutions.
- Support model serving through APIs, batch jobs, or real-time systems, and apply MLOps practices for versioning, orchestration, monitoring, and CI/CD.
- Troubleshoot data, model, deployment, and integration issues while maintaining clear technical documentation and participating in code reviews.
What do you need to have?
- Bachelor's degree in Computer Science, Engineering, Data Science, Software Engineering, Data Engineering, or a related technical field.
- 0-2 years of experience in machine learning, data science, data engineering, software engineering, or relevant hands-on academic, internship, personal, or professional projects.
- Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn, TensorFlow, or PyTorch.
- Understanding of the machine learning lifecycle and the ability to clearly explain a project, your personal contribution, the tools used, and the outcome.
- Basic familiarity with data pipelines, databases, APIs, software development practices, or workflow automation.
- Advanced technical and business English, both written and verbal.
- Ability to work onsite in Monterrey at least two days per week and support plant-based projects as needed.
What would be a plus?
- Exposure to Databricks, MLflow, Kubeflow, Docker, Kubernetes, CI/CD, or other MLOps/DevOps tools.
- Experience with manufacturing, industrial, process, plant, or production data.- A GitHub portfolio or other examples that demonstrate hands-on technical work.
What do we offer?
- Competitive benefits above the requirements of Mexican law.
- Opportunity to work on high-impact machine learning initiatives that support manufacturing and business transformation.
- Collaborative global environment with exposure to Data Science, IT, analytics, and manufacturing teams.
- Learning and career development in a growing technical organization.
Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodation to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodations related to disability or religion, please contact us at accommodations@corning.com