Kiddom
Machine Learning Engineer
Kiddom, San Francisco, California, United States, 94199
About KiddomKiddom is a groundbreaking educational platform that promotes student equity and growth by uniting high-quality instructional materials with dynamic digital learning. Through unparalleled curriculum management functionality, Kiddom empowers schools and districts to take ownership of their curriculum – resulting in learning experiences tailored to meet the unique needs and goals of local communities. Kiddom’s high-quality curriculum is layered with robust teacher and leader data insights to drive the continuous improvement of instructional decisions, school/district programming, and professional learning. You will work closely with other departments, including Product, Engineering, Machine Learning and Analytics, to understand and cater to their data and ML needs. You will also define and document data workflows, data and ML pipelines, and transformation processes for clear understanding and knowledge sharing. We are looking for someone with excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders. Do you have a strong understanding of PII compliance and best practices in data handling and storage? If you also exhibit strong problem-solving skills, with a knack for optimizing performance and ensuring data integrity and accuracy, we want to chat!
You Will...Design, build, and maintain scalable data pipelines to transform raw data into analytics-ready datasetsEnsure optimal performance, reliability, and efficiency of the data pipelinesIntegrate machine learning models into data pipelines to enhance analytics capabilitiesCollaborate with data scientists to deploy and monitor ML models in productionEnsure the scalability and reliability of ML workflows and infrastructureDevelop and optimize ML models for predictive analytics and data-driven decision-makingMonitor the data infrastructure for performance bottlenecks and implement optimizations as necessaryCollaborate with other engineering teams to ensure seamless data integration with high availability
What we look for...Bachelor's or Master's degree in Computer Science, Engineering, or a related field3+ years of experience as a data engineer, and 8+ years of software engineering experience (including data engineering)Expertise in using Amazon SageMaker for building, training, and deploying machine learning models.Knowledge of AWS Lambda for serverless execution of code, especially for model inference and lightweight processing tasks.Familiarity with AWS Glue or similar ETL tools (Extract, Transform, Load)Familiarity with Snowflake, RDS, Cassandra database services for structured data storage and querying. Proficiency in using Amazon S3 for data storage and retrieval, especially for large datasets used in machine learningKnowledge of AWS EC2 for scalable computing resources and ECS for containerized application deployment, useful for training and deploying models. Understanding of AWS Identity and Access Management (IAM) for managing permissions and securityFamiliarity with Amazon Kinesis for real-time data streaming and processingSkills in preprocessing and transforming raw data into a format suitable for machine learning using DBTExperience with CI/CD tools and practices for automating the deployment and monitoring of machine learning modelsKnowledge of AWS CloudWatch and AWS CloudTrail for monitoring model performance and logging eventsProficiency in using AWS CloudFormation or Terraform to manage and provision AWS resources programmaticallyStrong programming skills in PythonProficiency in SQL for querying databases and manipulating structured dataUnderstanding of security best practices in AWS, including data encryption and network securityKnowledge of AWS cost management and optimization strategies to ensure efficient use of resourcesExperience in developing and deploying APIs for model inference and interaction with other systems using AWS API Gateway and AWS Lambda
Salary and BenefitsSalary range is dependent on geography, past experience, seniority, and demonstrated role-related ability during the interview process. Full-time permanent employees are eligible for the following benefits:- Competitive salary- Meaningful equity- Health benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance- 10 paid sick days per year- Unlimited vacation time policy (subject to internal approval). Average use 4 weeks off per year.- Paid family leave for eligible employees
COVID Vaccination PolicyKiddom policy requires employees to be vaccinated before they visit an office or attend company events. We have remote roles but in certain positions where office attendance is deemed to be essential to the role, offers of employment shall be conditional upon proof of vaccination.
Potential Salary Range$150,000 - $200,000+
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You Will...Design, build, and maintain scalable data pipelines to transform raw data into analytics-ready datasetsEnsure optimal performance, reliability, and efficiency of the data pipelinesIntegrate machine learning models into data pipelines to enhance analytics capabilitiesCollaborate with data scientists to deploy and monitor ML models in productionEnsure the scalability and reliability of ML workflows and infrastructureDevelop and optimize ML models for predictive analytics and data-driven decision-makingMonitor the data infrastructure for performance bottlenecks and implement optimizations as necessaryCollaborate with other engineering teams to ensure seamless data integration with high availability
What we look for...Bachelor's or Master's degree in Computer Science, Engineering, or a related field3+ years of experience as a data engineer, and 8+ years of software engineering experience (including data engineering)Expertise in using Amazon SageMaker for building, training, and deploying machine learning models.Knowledge of AWS Lambda for serverless execution of code, especially for model inference and lightweight processing tasks.Familiarity with AWS Glue or similar ETL tools (Extract, Transform, Load)Familiarity with Snowflake, RDS, Cassandra database services for structured data storage and querying. Proficiency in using Amazon S3 for data storage and retrieval, especially for large datasets used in machine learningKnowledge of AWS EC2 for scalable computing resources and ECS for containerized application deployment, useful for training and deploying models. Understanding of AWS Identity and Access Management (IAM) for managing permissions and securityFamiliarity with Amazon Kinesis for real-time data streaming and processingSkills in preprocessing and transforming raw data into a format suitable for machine learning using DBTExperience with CI/CD tools and practices for automating the deployment and monitoring of machine learning modelsKnowledge of AWS CloudWatch and AWS CloudTrail for monitoring model performance and logging eventsProficiency in using AWS CloudFormation or Terraform to manage and provision AWS resources programmaticallyStrong programming skills in PythonProficiency in SQL for querying databases and manipulating structured dataUnderstanding of security best practices in AWS, including data encryption and network securityKnowledge of AWS cost management and optimization strategies to ensure efficient use of resourcesExperience in developing and deploying APIs for model inference and interaction with other systems using AWS API Gateway and AWS Lambda
Salary and BenefitsSalary range is dependent on geography, past experience, seniority, and demonstrated role-related ability during the interview process. Full-time permanent employees are eligible for the following benefits:- Competitive salary- Meaningful equity- Health benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance- 10 paid sick days per year- Unlimited vacation time policy (subject to internal approval). Average use 4 weeks off per year.- Paid family leave for eligible employees
COVID Vaccination PolicyKiddom policy requires employees to be vaccinated before they visit an office or attend company events. We have remote roles but in certain positions where office attendance is deemed to be essential to the role, offers of employment shall be conditional upon proof of vaccination.
Potential Salary Range$150,000 - $200,000+
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