Senior Machine Learning Engineer Job at ChatGPT Jobs in Washington
ChatGPT Jobs, Washington, DC, United States
Overview
Job Description
Senior Machine Learning Engineer at GiveCampus
Location : Washington, DC (Remote)
Salary : $118.40K - $162.50K/yr (Estimated pay)
Type : Full-time
Posted : 1 hour ago
About GiveCampus
GiveCampus is the world's leading fundraising platform for non-profit educational institutions. Trusted by 1,300+ colleges, universities, and K-12 schools, our mission is to help advance the quality, the affordability, and the accessibility of education.
Job Description
We're looking for a Senior ML Engineer to own the productionization and operational lifecycle of our machine learning models. You'll work closely with our Data Scientist, who focuses on customer discovery and prototype development, to take validated models from notebooks to production systems that serve predictions to our customers.
This is our
first ML Engineer position , and you will be instrumental in defining the direction of our ML Platform. This is a high-impact role where you'll shape how we build and operate ML systems.
Responsibilities
Model Productionization: Transform prototypes into production-ready Python code, containerize models, implement comprehensive testing.
Pipeline Development: Build automated training pipelines using SageMaker Pipelines and Step Functions; develop batch and real-time inference pipelines; integrate with Snowflake.
Deployment & Serving: Deploy models to SageMaker endpoints, configure batch transform jobs, integrate predictions with our Rails application.
Operations & Maintenance: Monitor model performance, build automated retraining pipelines, own incident response, optimize costs.
Platform & Tooling: Build reusable templates, libraries, and documentation for ML operations.
What We Are Looking For
5+ years of software engineering experience, with 3+ years focused on ML systems
Strong Python skills with emphasis on production code quality
Experience deploying and operating ML models in production environments
Hands-on experience with AWS (SageMaker preferred)
Proficiency with Docker and containerization
Understanding of ML concepts
Experience building data pipelines and working with data warehouses (Snowflake a plus)
Bonus Points
Experience with SageMaker Pipelines, Feature Store, Model Registry
Familiarity with Step Functions, EventBridge
Infrastructure as Code experience (Terraform, CDK, CloudFormation)
Experience with LLMs, RAG architectures, or generative AI applications
Experience integrating ML systems with web applications (Rails, APIs)
Background in B2B SaaS or EdTech
Tech Stack
ML Platform: AWS SageMaker
Data: Snowflake
Orchestration: Step Functions, EventBridge
Application: Rails
Infrastructure: AWS, Terraform
GiveCampus is an Equal Opportunity Employer.
#J-18808-Ljbffr
Job Description
Senior Machine Learning Engineer at GiveCampus
Location : Washington, DC (Remote)
Salary : $118.40K - $162.50K/yr (Estimated pay)
Type : Full-time
Posted : 1 hour ago
About GiveCampus
GiveCampus is the world's leading fundraising platform for non-profit educational institutions. Trusted by 1,300+ colleges, universities, and K-12 schools, our mission is to help advance the quality, the affordability, and the accessibility of education.
Job Description
We're looking for a Senior ML Engineer to own the productionization and operational lifecycle of our machine learning models. You'll work closely with our Data Scientist, who focuses on customer discovery and prototype development, to take validated models from notebooks to production systems that serve predictions to our customers.
This is our
first ML Engineer position , and you will be instrumental in defining the direction of our ML Platform. This is a high-impact role where you'll shape how we build and operate ML systems.
Responsibilities
Model Productionization: Transform prototypes into production-ready Python code, containerize models, implement comprehensive testing.
Pipeline Development: Build automated training pipelines using SageMaker Pipelines and Step Functions; develop batch and real-time inference pipelines; integrate with Snowflake.
Deployment & Serving: Deploy models to SageMaker endpoints, configure batch transform jobs, integrate predictions with our Rails application.
Operations & Maintenance: Monitor model performance, build automated retraining pipelines, own incident response, optimize costs.
Platform & Tooling: Build reusable templates, libraries, and documentation for ML operations.
What We Are Looking For
5+ years of software engineering experience, with 3+ years focused on ML systems
Strong Python skills with emphasis on production code quality
Experience deploying and operating ML models in production environments
Hands-on experience with AWS (SageMaker preferred)
Proficiency with Docker and containerization
Understanding of ML concepts
Experience building data pipelines and working with data warehouses (Snowflake a plus)
Bonus Points
Experience with SageMaker Pipelines, Feature Store, Model Registry
Familiarity with Step Functions, EventBridge
Infrastructure as Code experience (Terraform, CDK, CloudFormation)
Experience with LLMs, RAG architectures, or generative AI applications
Experience integrating ML systems with web applications (Rails, APIs)
Background in B2B SaaS or EdTech
Tech Stack
ML Platform: AWS SageMaker
Data: Snowflake
Orchestration: Step Functions, EventBridge
Application: Rails
Infrastructure: AWS, Terraform
GiveCampus is an Equal Opportunity Employer.
#J-18808-Ljbffr