Machine Learning Engineer, Kiddom
$150-200k
+ Equity
1+ day a week in office
Personalised teaching and learning for children
Open for applications
Personalised teaching and learning for children
21-100 employees
Open for applications
$150-200k
+ Equity
1+ day a week in office
21-100 employees
Company mission
To empower learners and teachers to achieve their full potential by connecting assessments, a digital curriculum, and instruction in one platform.
Role
Who you are
- 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!
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field
- 3+ 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 learning
- Knowledge 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 security
- Familiarity with Amazon Kinesis for real-time data streaming and processing
- Skills in preprocessing and transforming raw data into a format suitable for machine learning using DBT
- Experience with CI/CD tools and practices for automating the deployment and monitoring of machine learning models
- Knowledge of AWS CloudWatch and AWS CloudTrail for monitoring model performance and logging events
- Proficiency in using AWS CloudFormation or Terraform to manage and provision AWS resources programmatically
- Strong programming skills in Python
- Proficiency in SQL for querying databases and manipulating structured data
- Understanding of security best practices in AWS, including data encryption and network security
- Knowledge of AWS cost management and optimization strategies to ensure efficient use of resources
- Experience in developing and deploying APIs for model inference and interaction with other systems using AWS API Gateway and AWS Lambda
- Kiddom policy requires employees to be vaccinated before they visit an office or attend company events
What the job involves
- 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
- Design, build, and maintain scalable data pipelines to transform raw data into analytics-ready datasets
- Ensure optimal performance, reliability, and efficiency of the data pipelines
- Integrate machine learning models into data pipelines to enhance analytics capabilities
- Collaborate with data scientists to deploy and monitor ML models in production
- Ensure the scalability and reliability of ML workflows and infrastructure
- Develop and optimize ML models for predictive analytics and data-driven decision-making
- Monitor the data infrastructure for performance bottlenecks and implement optimizations as necessary
- Collaborate with other engineering teams to ensure seamless data integration with high availability
Our take
Digital education has become an increasing reality in recent years. Whilst services such as Zoom have provided platforms for remote teaching, the minimal functionality of such services has outlined the lack of digital engagement tools that classrooms require.
Kiddom develops a collaborative learning platform for K-12 schooling that aims to provide integrated solutions to not only remote teaching but also in-person school and homework assignments. The platform allows teachers to assign tasks and to collaborate with students on them, whilst the software gathers data to provide insights on student engagement and performance.
The startup currently provides its services to individual teachers for free, but solutions for inter-institutional curriculums come at an annual subscription fee. Kiddom’s approach aims to provide solutions and fill the gap between remote and in-school teaching, at the same time as integrating student analytics to optimize and personalize the way students are educated.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Aug 2021
$35m
SERIES C
Mar 2018
$15m
SERIES B
Total funding: $56.5m
Company benefits
- Competitive salary
- Meaningful equity
- Remote friendly culture with budget to make sure you can work comfortably from home or office
- Health benefits: medical, dental, vision, disability and life insurance
- Flexible vacation policy
Company HQ
Financial District, San Francisco, CA
Articles
Leadership
Ahsan Rizvi
(CEO)After an MSc at the University of Illinois, Ahsan spent a year as a Fulton Collective LLC Partner, before co-founding Le Sensor in 2010. They leveraged this entrepreneurial experience to found Kiddom in January 2015, serving since as CEO.
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