ML Engineer - End-to-End Model Lifecycle & Production

Merik Solutions; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Merik Solutions is seeking a senior ML engineer to own the full model lifecycle from data preparation to deployment and monitoring. You will deliver reliable ML systems for forecasting, classification, and recommendation use cases, emphasizing MLOps as much as model accuracy.

The role requires hands-on experience with Python, SQL, and cloud ML platforms, plus the ability to communicate trade-offs to non-technical stakeholders. Travel and remote-work details not specified.

Qualifications

• 4+ years in ML engineering or applied data science.
• Strong Python and SQL with production ML experience.
• Experience with at least one major cloud ML stack (SageMaker, Vertex AI, or Azure ML).
• Solid understanding of feature engineering, evaluation, and experiment design.
• Authorization to work in the United States.

Responsibilities

• Train, evaluate, and deploy ML models for forecasting, classification, and recommendation use cases.
• Build reproducible training pipelines and feature stores.
• Set up model monitoring, drift detection, and automated retraining.
• Work with client data teams to productionize prototypes.
• Present model behavior and trade-offs to non-technical stakeholders.

Skills

Python

SQL

ML engineering

Production ML

Experiment design

Tools

SageMaker

Vertex AI

Azure ML

Job description

Merik Solutions is seeking a senior ML engineer to own the full model lifecycle from data preparation to deployment and monitoring. You will deliver reliable ML systems for forecasting, classification, and recommendation use cases, emphasizing MLOps as much as model accuracy.

The role requires hands-on experience with Python, SQL, and cloud ML platforms, plus the ability to communicate trade-offs to non-technical stakeholders. Travel and remote-work details not specified.