Senior Machine Learning Engineer

cambridge university press & assessment; Philippines; On-site; PHP 1,160,640 - 1,584,720; Full time

Benefits offered by this job

HMO & insurance

Paid annual leaves

Retirement package

Career growth

Well-being programs

Hybrid schedule

Diverse collaboration

Job summary

Cambridge University Press & Assessment in Makati City seeks a Senior Machine Learning Engineer to lead the design, architecture and deployment of transformer-based NLP models for automated marking.

You will own the end-to-end ML lifecycle, mentor engineers, and collaborate with cross-functional teams. The role offers a hybrid work arrangement, permanent employment, and a pay range of PHP 104,000 to 142,000 monthly.

Qualifications

• Technical Authority: Significant commercial experience developing, deploying, and maintaining production-grade ML and NLP systems at scale.
• Advanced NLP Expertise: Experience with modern deep learning frameworks and transformer architectures.
• Full-Lifecycle Engineering: Strong Python software engineering across data prep, training pipelines, deployment and monitoring.
• Technical Leadership: Ability to independently drive complex technical initiatives and influence direction.

Responsibilities

• ML Strategy & Leadership: Establish team-wide engineering standards for model architecture and evaluation frameworks.
• Model Development & Innovation: Design, train and optimize NLP solutions to score candidate responses and enable multi-criteria systems.
• Evaluation & Bias Mitigation: Build robust experiments to assess fairness, consistency, and drift against expert judgment.
• Lifecycle Ownership: Manage end-to-end ML lifecycle from conception to cloud deployment and monitoring.
• Mentorship & Communication: Guide engineers, support roadmap planning, and explain complex concepts to non-technical stakeholders.

Skills

NLP

PyTorch

TensorFlow

Python

ML lifecycle

Cloud deployment

Technical leadership

Job description

Senior Machine Learning Engineer

Work setup: We operate in a hybrid work environment, and we encourage applicants who are open to working in the office two days a week.

Work schedule: Monday to Friday, 10AM to 6PM Manila time

Employment type: Permanent

Location: Makati City, Metro Manila

Pay range: Php 104,000 to Php 142,000

Discover a world of endless possibilities with Cambridge University Press & Assessment, a distinguished global academic publisher and assessment organization proudly affiliated with the prestigious University of Cambridge.

We are looking for a dedicated Senior Machine Learning Engineer to join our Automarking for Digital Assessments (ADA) team. In this role, you will act as the technical authority for machine learning, leading the design, architecture, and deployment of transformer-based NLP models which enables reliable marking behavior.

Why Cambridge?

Cambridge University Press & Assessment is a world-renowned not-for-profit academic publisher and assessment organisation, proudly part of the prestigious University of Cambridge. With a legacy rooted in over 800 years of educational excellence, we are dedicated to unlocking the potential of learners and educators across the globe.

Joining Cambridge's second largest global office in the Philippines —operating for over 22 years with 1,300+ colleagues— means becoming a part of an extraordinary institution renowned worldwide. We are recognised as a Great Place to Work® for three consecutive years, reflecting our inclusive culture, strong sense of purpose, and commitment to the professional growth and well‑being of our people. At Cambridge, we don't just publish books or deliver tests—we empower progress, inspire curiosity, and champion the pursuit of knowledge.

What can you get from Cambridge?

At Cambridge, you'll become a part of a vibrant and forward-thinking community that transcends tradition, fostering a culture of continuous growth and personal development. Here, we provide the right environment for you to thrive, supporting your professional journey and empowering you to reach your highest potential, that is why our pay philosophy is intricately tied to your skills and competencies, ensuring that your compensation aligns with the unique value you bring to the role you are applying for.

• Regular Employment on Day 1
• HMO Coverage and Life Insurance on Day 1
• Paid Annual Leaves (Vacation, Well-being, Flexible, Holiday, and Volunteering leaves)
• Vesting/Retirement package
• Opportunities for career growth and development
• Access to well-being programs
• Flexible schedule, hybrid work arrangement and work-life balance
• Opportunity to collaborate with colleagues from diverse branches that will expand your horizons and enrich your understanding of different cultures

What will you do as a Senior Applied Machine Learning Engineer?

Reporting to the Automarking for Digital Assessments Team Lead, your accountabilities will include:

• ML Strategy & Leadership: Serve as the principal ML subject-matter expert, establishing team-wide engineering standards for model architecture, validation frameworks, and performance optimization.
• Model Development & Innovation: Design, train, and optimize advanced NLP solutions to score candidate responses, while leading the R&D of future multi-criteria and extended response systems.
• Evaluation & Bias Mitigation: Partner with assessment specialists to build robust experimentation frameworks, assessing model fairness, consistency, and drift against expert human judgment.
• Lifecycle Ownership: Own the end-to-end machine learning lifecycle from conception and pipeline creation through to cloud deployment, production monitoring, and documentation.
• Mentorship & Communication: Mentor engineers in best practices, support roadmap planning, and translate highly complex technical concepts for non-technical stakeholders.

What makes you the ideal candidate for this role?

An ideal candidate has the following qualities:

Essential:

• Technical Authority: Significant commercial experience developing, deploying, and maintaining production-grade machine learning and NLP systems at scale.
• Advanced NLP Expertise: Extensive experience building solutions with modern deep learning frameworks (e.g., PyTorch, TensorFlow) and transformer-based architectures.
• Full-Lifecycle Engineering: Strong Python software engineering skills covering the full ML lifecycle—from data preparation and training pipelines to deployment and monitoring.
• Technical Leadership: Proven ability to independently lead complex technical initiatives and successfully influence technical direction without direct managerial authority.

Desirable:

• Automated Scoring Systems: Experience evaluating ML systems against expert human decision-making, or building automated scoring, ranking, and classification platforms.
• EdTech & Psychometrics: Background in educational technology, assessment platforms, or familiarity with psychometric concepts.
• Inference Optimization: Experience working with high-performance machine learning APIs and cloud-based inference services.

For the selection process, note that there may be a technical interview to assess your skills that can include a take-home task.