Remote ML Forecasting Platform Engineer

Dahl Consulting; Minneapolis (MN); Hybrid; USD 156,000 - 188,000; Full time

Benefits offered by this job

Benefits package

Job summary

Dahl Consulting is seeking a Development Engineer to design, implement, and support large-scale forecasting platforms in a remote contract role. You will work with data scientists and platform teams to productionize research, build ML pipelines, and scale time-series models.

Responsibilities include deploying forecasting solutions, optimizing data pipelines, and ensuring reliability in cloud environments. Remote-first role with limited onsite attendance for local candidates, and collaboration

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field; or equivalent practical experience.
• Experience building and deploying machine learning models in production environments.
• Hands‑on experience with time-series forecasting methodologies such as Prophet, ARIMA, or similar frameworks.
• Strong understanding of model validation, experiment tracking, and hyperparameter tuning.
• Experience with feature engineering and feature store concepts.
• Proficiency in Python and software development best practices.
• Experience working with distributed data processing technologies such as Spark, Dask, Ray, or similar platforms.
• Demonstrated ability to transform and scale large datasets using PySpark.
• Experience designing and optimizing data pipelines for performance, reliability, and cost efficiency.
• Working knowledge of analytical data platforms such as BigQuery, including dataset design, partitioning, clustering, and data validation.
• Experience building and maintaining machine learning pipelines using Kubeflow Pipelines (KFP), Vertex AI, Airflow, or similar orchestration platforms.
• Understanding of pipeline architecture, workflow orchestration, caching strategies, and configuration management.
• Experience using Git-based version control and structured change management processes.
• Familiarity with testing frameworks, dependency management tools, and code quality practices.
• Experience working with cloud platforms such as Google Cloud Platform (GCP), AWS, or Azure.
• Knowledge of containerization and orchestration technologies including Docker and Kubernetes.
• Experience implementing CI/CD pipelines and deployment automation.
• Understanding of secrets management and secure environment configuration.

Responsibilities

• Build, deploy, and maintain machine learning solutions in production environments.
• Develop and optimize time-series forecasting models and supporting data pipelines.
• Convert and scale data-processing workloads from pandas-based frameworks to PySpark and other distributed processing technologies.
• Design and implement ML pipelines using orchestration tools such as Kubeflow Pipelines, Vertex AI, or Airflow.
• Integrate data validation, model training, testing, and deployment processes into automated workflows.
• Optimize data pipelines and storage solutions for scalability, performance, and cost efficiency.
• Collaborate with data science teams to productionize research and analytics solutions.
• Maintain and enhance existing Python applications and codebases following software engineering best practices.
• Build and support CI/CD processes for machine learning workflows and platform deployments.
• Implement cloud-native solutions leveraging Google Cloud Platform (GCP) services and containerized environments.
• Monitor system performance, troubleshoot production issues, and improve operational reliability.
• Contribute to architecture decisions that support enterprise-scale forecasting and fulfillment systems.

Skills

Python

Time-series forecasting

Prophet/ARIMA models

Git-based version control

Production ML pipelines

Distributed data processing

Education

Bachelor's degree or equivalent practical experience

Tools

Kubeflow Pipelines

Vertex AI

Airflow

PySpark

Docker

Kubernetes

BigQuery

Terraform

Job description

Dahl Consulting is seeking a Development Engineer to design, implement, and support large-scale forecasting platforms in a remote contract role. You will work with data scientists and platform teams to productionize research, build ML pipelines, and scale time-series models.

Responsibilities include deploying forecasting solutions, optimizing data pipelines, and ensuring reliability in cloud environments. Remote-first role with limited onsite attendance for local candidates, and collaboration