ApplyBoard simplifies the study abroad search, application, and acceptance process by connecting international students, recruitment partners, and educational institutions on one intuitive and personalized platform. ApplyBoard is a mission-driven, hyper-growth organization. It has been attracting dedicated individuals for more than eight years who are inspired every day to break down barriers to international education and take their careers to new heights at a company that will invest in their career growth. Our
six core values
are our compass in our mission to Educate the World and the foundation of our unique company culture. As an organization built on a foundation of diversity, it’s important that our team members are representative of the students from more than 150 countries that we support.
The Role
As part of the ApplyBoard AI team, your mission is to help develop and productionize AI services and capabilities that help other teams to advance their services for students and recruitment partners.
You will be a senior member of a team that delivers AI capabilities to help other teams. As a Senior Machine Learning Engineer, you value collaboration and nurture innovation while working in an energetic team. Your strong foundation in productionizing machine learning models will be valuable in enabling a data-driven culture company-wide. You are expected to work on continuous improvement of our best practices for AI services and ensuring that our models are accurate, reliable, and explainable.

Responsibilities

• Developing and productionizing new machine learning models
• Building and documenting APIs
• Improving the machine learning development & deployment pipeline
• Maintaining existing machine learning models
• Performing statistical analysis of model performance
• ML Ops and collaboration with DevOps
• Building internal demos and dashboards of our products to get feedback from different departments

Qualifications

• 7+ years of experience in software engineering or back-end engineering
• 5+ years of experience in productionizing machine learning (ML) systems
• In-depth understanding of researching, designing, developing, and deploying ML systems, models, and schemes
• Hands-on experience of deploying ML models/systems to AWS infrastructure
• Performing statistical analysis and using results to improve models
• Training and retraining ML systems and models as needed
• Experience with Python, Docker containers, and AWS CDK deployment
• Familiarity with ML frameworks and libraries
• Experience of development and deployment with AWS Bedrock
• Strong analytical and problem solving skills
• Ability to communicate effectively with people who are both highly technical, and non-technical alike
• Driven, passionate and creative, and thrives in a fast-paced environment

Ideally, you also have experience with many of:

• AWS Machine Learning Specialty Certificate
• Jenkins, CodeBuild, Terraform, Helm Charts
• AWS API Gateway, CloudFront, Lambda
• Data Pipeline, Kubernetes, New Relic
• Microservices, Kinesis, Kafka

About ApplyBoard
ApplyBoard empowers students around the world to access the best education. With more than 1,000,000 students from over 150 countries helped with their journey in less than a decade, we are just getting started.
ApplyBoard’s 1,200 global team members in 30 countries assist students and our 1,500 partner institutions by empowering the international student sector with innovative technology and insights. As a five-time consecutive Deloitte Fast 50 and Fast 500 ranked company, ApplyBoard is growing and scaling like few other companies. On top of our strong growth, our people are growing personally and professionally. ApplyBoard India was Great Place to Work® Institute (India) certified for outstanding employee experience and workplace culture.
Thank you for your interest in joining the ApplyBoard Team and being part of our mission to Educate the World. While we are lucky to attract a high level of interest in each of our roles, only qualified applicants will be contacted and selected for an interview.
ApplyBoard welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates in all aspects of the hiring and selection process

• Developing and productionizing new machine learning models
• Building and documenting APIs
• Improving the machine learning development & deployment pipeline
• Maintaining existing machine learning models
• Performing statistical analysis of model performance
• ML Ops and collaboration with DevOps
• Building internal demos and dashboards of our products to get feedback from different department