Senior Software Engineer - Data & ML | WFH | Day Shift | Weekends Off

Engineer Smarter Learning for Australia's Education Technology Sector

Education technology matters most when it helps teachers act with confidence. In the Senior Software Engineer - Data & ML role, you'll develop scalable services and ML infrastructure that translate learning data into practical support. Your work will reach schools across Australia, with strong technical collaboration, meaningful ownership, and a rewarding long-term global career at Emapta for top 1% talent. Snapshot

• Employment Type: Full-time
• Work Setup: Permanent Work From Home
• Shift: Day Shift, 10:00 AM-7:00 PM Melbourne Time, Weekends OffBenefits
• Day 1 HMO coverage with free dependent

Competitive Salary Package

Day Shift

schedule

• Fixed weekends off
• Permanent WFH arrangement

Salary Advance Program through our banking partner (Eligibility and approval subject to bank assessment. Available to account holders with minimum of 6 months company tenure.)Unlimited upskilling through Emapta Academy courses (Want to know more? Visit: https://emapta.com/training-calendar/)Free 24/7 access to our office gyms (Ortigas and Makati) with a free physical fitness trainer! Exclusive Emapta Lifestyle perks (hotel and restaurant discounts, and more!)Unlimited opportunities for employee referral incentives across the organization

Standard government and Emapta

benefits

• Total of 20 annual leaves to be used on your own discretion (including 5 credits convertible to cash)
• Fun engagement activities for employees
• Mentorship and exposure to global leaders and teams
• Career growth opportunities
• Diverse and supportive work environment
• Qualifications3-5 years of relevant software engineering experience
• Strong Python engineering skills and experience with data and ML libraries such as Pandas, PySpark, Scikit-learn, and MLflow
• Backend development expertise with Fast
• API, Django, Flask, or an equivalent framework, including API design and data system integration

Experience developing ETL workflows and data pipelines with tools such as Airflow, Dagster, dbt, and n8nStrong understanding of data modeling and warehousing using SQL, Duck

• DB, and Parquet
• Experience deploying and scaling batch and real-time ML models in production
• Familiarity with AWS data and compute services, including S3, Glue, Lambda, Step Functions, ECS/Fargate, and RDS or Redshift
• Experience with CI/CD, Docker, and Infrastructure as Code using Terraform or Cloud

Formation

• Strong knowledge of data privacy, security, and compliance practices
• Experience implementing observability for backend and ML systems, including monitoring dashboards and logging
• Excellent communication, problem-solving, and cross-functional collaboration skills
• Experience improving engineering and data practices and mentoring peers
• Curiosity about emerging data and ML technologies and their applications in education

Responsibilities

Feature and Platform Development

Build backend features and services that use data and ML insights to improve learning and assessment experiences. Collaborate with product and design teams to develop data-driven platform features. Contribute to shared libraries, APIs, and infrastructure that support rapid, reliable feature delivery. Data Platform and ML Infrastructure

Design, build, and maintain data pipelines and services for analytics, reporting, and ML use cases. Collaborate with data scientists on feature engineering, model training pipelines, deployment, monitoring, and retraining. Establish best practices for model lifecycle management, reproducibility, and production performance. Backend Engineering for Data Systems

Develop APIs and batch and streaming systems that process large volumes of educational and behavioral data. Optimize transactional and analytical workloads for performance, reliability, and scalability. Integrate data and ML outputs into user-facing systems through well-structured backend interfaces. Data Governance, Quality, and Security

Implement data validation, quality assurance, and lineage tracking to maintain trust in key data assets. Technical Architecture and Strategy

Help define the long-term architecture for data-driven and ML-enabled systems aligned with the platform's learning outcomes vision. Evaluate and integrate emerging data and ML technologies to improve scalability, observability, and developer productivity. Balance innovation with maintainability and operational excellence. Collaboration and Mentorship

Work with engineers, data scientists, and product managers to translate business requirements into scalable, data-centric features. Mentor peers in software, data, and ML engineering best practices. Promote collaboration between feature and data teams. About the Client

Our client is an Australian education technology company helping schools turn everyday learning into measurable progress. Its curriculum-aligned lessons, purposeful practice, and actionable insights support more than 1,000 schools, 17,000 teachers, and 200,000 students across Australia. Built on a decade of innovation and insights from over 1.7 billion data points, its platform helps educators identify learning needs and guide better decisions. Here, your engineering work contributes to a proven system that makes quality education more effective at scale each day. Join the Top 1% Talent. A better career. A better life. Welcome to Emapta Philippines: home to professionals who choose growth, balance, and impact. Recognized as one of HR Asia's Best Companies to Work For in Asia 2025 and winner of Inspiring Workplaces Australasia 2026, Emapta offers more than opportunities -- it provides a career environment where people thrive. Collaborate with global teams, build meaningful expertise, and grow in a culture that prioritizes both performance and well-being. Apply now and experience the difference!