ML & MLOps Engineer — Real-Time Scoring & Pipelines

HCLTech; San Antonio (TX); On-site; USD 100,000 - 148,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

Employee assistance program

401(k) retirement plan

Paid time off

Paid holidays

Job summary

HCLTech is seeking a highly talented Machine Learning Implementation Engineer / MLOps Engineer to join our team in advancing the technological world through innovation and creativity. This is a full-time onsite role in the United States.

You will support end-to-end ML model deployment, design pipelines with Python and SQL, set up OpenShift and Docker, and collaborate with data scientists, data engineers, model owners, platform teams, governance teams, and business stakeholders to deliver

Qualifications

• Hands-on experience implementing and operating ML models in enterprise environments.
• Strong Python and SQL skills with experience building ML pipelines.
• Familiarity with OpenShift, Docker, GitLab, Snowflake, Kafka, DBT and Control‑M.

Responsibilities

• Support end-to-end ML model implementation, deployment, and operationalization.
• Design and enhance ML pipelines using Python, SQL and enterprise frameworks.
• Set up OpenShift, Docker, service accounts, libraries and model artifacts.
• Develop and monitor Control‑M workflows for data prep, batch scoring and execution.
• Build data pipelines with Snowflake and relational databases; ensure real-time scoring.
• Support CI/CD deployment, production releases, testing and incident resolution.
• Maintain runbooks, diagrams and handover materials; collaborate with stakeholders.

Skills

Python

SQL

ML pipelines

MLOps

CI/CD

OpenShift

Docker

GitLab

Snowflake

Kafka

DBT

Control-M

Tools

OpenShift

Docker

GitLab

Snowflake

Kafka

DBT

Control‑M

Job description

HCLTech is seeking a highly talented Machine Learning Implementation Engineer / MLOps Engineer to join our team in advancing the technological world through innovation and creativity. This is a full-time onsite role in the United States.

You will support end-to-end ML model deployment, design pipelines with Python and SQL, set up OpenShift and Docker, and collaborate with data scientists, data engineers, model owners, platform teams, governance teams, and business stakeholders to deliver