Production ML Engineer: Build & Deploy Advanced Models

Flexm; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Flexm is seeking a Sr and Jr Machine Learning Engineer to design, develop, deploy, and continuously improve ML models that solve complex business problems using large-scale structured and unstructured data.

The ideal candidate will have strong experience building production-grade machine learning systems, developing predictive and behavioural models, and collaborating with data engineering and software development teams to operationalize AI solutions.

Qualifications

• Experience designing, training, validating, and deploying ML models.
• Hands-on experience with classification, regression, clustering, anomaly detection, and forecasting.
• Strong feature engineering, model evaluation, and hyperparameter tuning.
• Advanced Python and Strong SQL and data analysis skills.
• Experience with Scikit-Learn, XGBoost, LightGBM, TensorFlow or PyTorch.
• Experience working with large datasets and building data-driven solutions.
• Familiarity with Spark/PySpark is preferred.
• Experience deploying ML solutions on AWS and cloud ML workflows.
• Familiarity with Docker, CI/CD, and model monitoring.

Responsibilities

• Design, develop, train, validate, and optimize machine learning models.
• Build classification, regression, clustering, ranking, recommendation, anomaly detection, and forecasting models.
• Perform feature engineering, feature selection, model tuning, and model evaluation.
• Conduct experimentation and statistical analysis to improve model performance.
• Develop models that identify behavioural patterns, trends, anomalies, and relationships within large datasets.
• Develop predictive models using historical data.
• Build scoring frameworks and risk prediction models.
• Develop propensity, segmentation, and forecasting models.
• Develop graph-based analytics and relationship detection models.
• Perform hyperparameter tuning and model optimization.
• Compare model performance across different algorithms and approaches.
• Continuously improve accuracy, precision, recall, and explainability.
• Deploy machine learning models into production environments.
• Implement model monitoring, performance tracking, drift detection, retraining, and version control.
• Collaborate with engineering teams to integrate models into production systems and APIs.
• Work closely with Data Engineers to define data requirements and data quality standards.
• Collaborate with Software Engineers to operationalize machine learning solutions.
• Partner with business stakeholders to translate requirements into machine learning solutions.

Skills

Model design

Model deployment

Experimentation

Python

SQL

Cloud ML

MLOps

Feature engineering

Model evaluation

Production ML

Tools

Scikit-Learn

XGBoost

LightGBM

TensorFlow

PyTorch

Spark

PySpark

Docker

CI/CD

SageMaker

Lambda

AWS

S3

Job description

Flexm is seeking a Sr and Jr Machine Learning Engineer to design, develop, deploy, and continuously improve ML models that solve complex business problems using large-scale structured and unstructured data.

The ideal candidate will have strong experience building production-grade machine learning systems, developing predictive and behavioural models, and collaborating with data engineering and software development teams to operationalize AI solutions.