Senior Machine Learning Engineer - 7416

etechnology; Manila; On-site; PHP 104,000 - 142,000; Full time

Benefits offered by this job

Day 1 Employment

HMO & Life Insurance

Paid Annual Leaves

Retirement Package

Career Growth

Well-being Programs

Flexible Hybrid Schedule

Cross-Branch Collaboration

Job summary

Cambridge University Press & Assessment in Manila is seeking a Senior Applied Machine Learning Engineer to advance our NLP scoring and assessment platforms. The role blends research with production engineering, working in a hybrid setup two days in the office to deliver scalable ML solutions.

You will lead ML strategy, develop models in PyTorch or TensorFlow, oversee end-to-end lifecycle from data to deployment, and mentor engineers while communicating complex concepts to non-technical

Qualifications

• Proven experience delivering production-grade ML/NLP systems.
• Experience with PyTorch or TensorFlow and transformer models.
• Strong Python engineering across data prep, training, deployment, and monitoring.
• Ability to lead complex technical initiatives.

Responsibilities

• Define ML strategy and establish engineering standards for model architectures and validation.
• Design, train, and optimize NLP solutions to score candidate responses and lead R&D of future systems.
• Build robust experimentation frameworks assessing fairness, consistency and drift.
• Own end-to-end ML lifecycle from conception to cloud deployment and monitoring.
• Mentor engineers and translate complex concepts for non-technical stakeholders.

Skills

ML leadership

NLP expertise

Python development

Communication

Tools

PyTorch

TensorFlow

Job description

SeniorMachine 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 to apply.

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

issalary range to apply.

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.

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.

The organization offers a wide range of benefits and opportunities including:

• 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.

Please review the attached job description for further details on the role.

What makes you the ideal candidate for this role?

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.

#LI-Hybrid #PursuingPotential #CambridgeManila