ML Engineer: Build Production-Grade ML Pipelines

Promantus Inc; Plano (TX); On-site; USD 140,000 - 180,000; Full time

Job summary

Promantus Inc in Plano, TX, is seeking an ML Engineer with hands-on software engineering skills in Python, PySpark, and Databricks to build end-to-end ML and data pipelines in production.

You will work with Spark, Kafka, Snowflake, MongoDB, PostgreSQL and Azure cloud, design SCD/temporal data models, implement Delta Lake/MLflow workflows, and contribute API services using FastAPI. GenAI experience is a plus, but classical ML/DS exposure is required.

Qualifications

• Strong Python development with production-ready ML pipelines.
• Experience with PySpark, Databricks, Spark, and streaming with Kafka.
• Experience with SQL and No-SQL databases (PostgreSQL, MongoDB).
• Knowledge of Delta Lake, MLflow, and workflow orchestration.
• Experience building production-grade data and ML pipelines.
• Experience API development (FastAPI).
• GenAI/Agents experience is a plus; however classic ML/DS exposure required.

Responsibilities

• Develop and maintain production-grade ML and data pipelines.
• Collaborate with ML/DS teams to deploy models in production.
• Design data models and data quality checks for SCD/temporal mappings.
• Build API services and interfaces (FastAPI) for model serving.
• Work with Delta Lake, MLflow, and orchestration tools.

Skills

Python

PySpark

Databricks

Spark

Kafka

Snowflake

MongoDB

PostgreSQL

Redis

Azure

FastAPI

ML pipelines

Data pipelines

ML workflows

Delta Lake

MLflow

GenAI

ELK

Job description

Promantus Inc in Plano, TX, is seeking an ML Engineer with hands-on software engineering skills in Python, PySpark, and Databricks to build end-to-end ML and data pipelines in production.

You will work with Spark, Kafka, Snowflake, MongoDB, PostgreSQL and Azure cloud, design SCD/temporal data models, implement Delta Lake/MLflow workflows, and contribute API services using FastAPI. GenAI experience is a plus, but classical ML/DS exposure is required.