Senior AI Engineer - Hybrid

enablesGROUP; Metro Manila; Hybrid; PHP 1,200,000 - 2,400,000; Full time

Benefits offered by this job

Health insurance

Laptop provided

Office in Pasig

Learning & development programs

Career advancement

Job summary

enablesGROUP is hiring a Senior AI Engineer in Ortigas, Pasig, PH. The role focuses on building, deploying, and maintaining AI/ML models and pipelines within the Data Analytics & AI team.

You will own AI/ML workstreams from development to production, ensuring solutions are robust, scalable, and enterprise-grade. The ideal candidate thrives on applied AI, prototyping Generative AI use cases, and improving production ML pipelines with strong software discipline.

Qualifications

• 2+ years' experience in data science, machine learning engineering, or applied AI required.
• Strong proficiency in Python and core ML libraries (scikit-learn, PyTorch, TensorFlow, Hugging Face) required.
• Hands-on experience with Databricks (MLflow, notebooks, Unity Catalog) required.
• Practical experience building and deploying Generative AI solutions (LLMs, RAG, prompt engineering) strongly preferred.
• Experience with Azure cloud services (Azure OpenAI, Azure ML, Azure Data Factory) required.
• Solid understanding of MLOps principles, including CI/CD for ML, model versioning, experiment tracking, and production monitoring required.
• Strong software engineering fundamentals, including Git, testing, and code reviews required.
• Familiarity with SQL and data modelling concepts (medallion/ star schema) preferred.
• Experience with structured and unstructured data in a cloud data platform environment preferred.
• Experience in regulated industries (life sciences, healthcare, pharma) preferred.
• Strong analytical and problem-solving skills; ability to work autonomously on complex challenges.
• Good written and verbal communication skills; ability to present findings to technical and non-technical audiences.

Responsibilities

• Design, develop, and deploy machine learning and AI models across use cases including predictive analytics, NLP, classification, and Generative AI.
• Write clean, production-quality Python code adhering to engineering standards.
• Leverage Databricks (MLflow, Feature Store, Model Serving) and Azure AI services to build scalable ML solutions.
• Build and maintain robust ML pipelines covering data prep, feature engineering, training, evaluation, and deployment using CI/CD and IaC.
• Implement monitoring and alerting for deployed models, including drift detection and retraining triggers.
• Contribute to MLOps toolchain improvements to ensure efficiency and reproducibility.
• Conduct exploratory data analysis and rapid prototyping to assess new AI/ML use cases.
• Collaborate with data engineers and the Data Platform Manager to meet pipeline requirements.

Skills

Python

ML engineering

Data science

Applied AI

Azure cloud services

Databricks MLflow

CI/CD for ML

Git

NLP

RAG pipelines

Tools

Databricks

Azure OpenAI

Azure ML

MLflow

Unity Catalog

Python notebooks

Job description

Why Join enablesGROUP?
Since 2016, enablesGROUP has been on a mission: to deliver high-quality operations and outsourcing services to every client, big or small.
Fast forward to 2026, we’ve grown our global footprint to serve 100+ clients and expanded into 4 key industries. At enablesGROUP, you’re not just joining a company – you’re joining a community that values growth, learning, and success. Check us out at www.enablesgroup.com.
At enablesGROUP, you’re not just joining a company – you’re joining a community that values growth, learning, and success.

We have market leading engagement scores and invest heavily in your Learning and Development, with a specific focus on enhancing your ability to leverage AI in your daily tasks.

Our Perks & Benefits include:

• Comprehensive health and life insurance starting Day 1, covering 2 eligible dependents.
• 20 leave credits for vacation, emergencies, sick days, and even your birthday!
• Endless opportunities for career advancement with annual performance reviews and salary increases.
• Company-provided laptop to set you up for success.
• Convenient office location in Pasig, at the heart of Manila, accessible to all.
• Loyalty rewards: Employees celebrating 5 years could receive a profit-sharing scheme.
• In-house learning & development programs with access to the latest in AI and technology.

Job Title: Senior AI Engineer
Location: Ortigas, Pasig, PH
Work Schedule: Monday to Friday, 4:00 PM to 1:00 AM PH Time (Hybrid | 3x Onsite, 2x WFH)

Job Summary

The Senior AI Engineer is a hands-on technical role responsible for building, deploying, and maintaining AI and machine learning models and pipelines that deliver tangible value to business operations. Working within the Data Analytics & AI team, this individual will take ownership of AI/ML workstreams from development through to production, ensuring solutions are robust, scalable, and aligned with enterprise standards.

The ideal candidate is a skilled engineer with a passion for applied AI and someone who is equally comfortable prototyping a new Generative AI use case as they are optimising a production ML pipeline. They bring strong software engineering discipline to data science, and thrive in collaborative, cross-functional environments.

Job Responsibilities:

AI/ML Model Development & Deployment

• Design, develop, and deploy machine learning and AI models across a range of use cases, including predictive analytics, NLP, classification, and Generative AI (e.g., LLM-powered agents, RAG pipelines).
• Write clean, well-tested, production-quality Python code, adhering to the team's engineering standards and best practices.
• Leverage Databricks (including MLflow, Feature Store, and Model Serving) and Azure AI services to build and operationalise scalable ML solutions.

MLOps & Pipeline Engineering

• Build and maintain robust ML pipelines covering data preparation, feature engineering, model training, evaluation, and deployment using CI/CD and Infrastructure as Code (IaC) practices.
• Implement monitoring and alerting for deployed models, including drift detection, performance tracking, and automated retraining triggers.
• Contribute to the continuous improvement of the team's MLOps toolchain and processes, ensuring efficiency and reproducibility.

Data Exploration & Experimentation

• Conduct exploratory data analysis and rapid prototyping to assess the feasibility and potential impact of new AI/ML use cases.
• Design and run experiments to evaluate model performance, applying rigorous statistical methods and clear documentation of findings.
• Collaborate with data engineers and the Data Platform Manager to ensure data pipelines and feature sets meet the requirements of AI/ML workloads.

Collaboration & Knowledge Sharing

• Partner with business stakeholders, analysts, and the BI team to understand requirements and translate them into well-defined AI/ML problem statements.
• Contribute to internal knowledge sharing through documentation, code reviews, tech talks, and training sessions to raise AI literacy across the organisation.
• Support the Lead AI Engineer in evaluating new tools, frameworks, and approaches, providing hands-on technical input and proof-of-concept development.

Qualifications:

• 2+ years' experience in data science, machine learning engineering, or applied AI required
• Strong proficiency in Python and core ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, Hugging Face) required
• Hands-on experience with Databricks (including MLflow, notebooks, and Unity Catalog) required
• Practical experience building and deploying Generative AI solutions (e.g., LLMs, RAG, prompt engineering) strongly preferred
• Experience with Azure cloud services (e.g., Azure OpenAI, Azure ML, Azure Data Factory) required
• Solid understanding of MLOps principles, including CI/CD for ML, model versioning, experiment tracking, and production monitoring required
• Strong software engineering fundamentals, including version control (Git), testing, and code review practices required
• Familiarity with SQL and data modelling concepts (e.g., medallion architecture, star schema) preferred
• Experience working with structured and unstructured data in a cloud data platform environment preferred
• Experience within regulated industries (life sciences, healthcare, or pharma) preferred
• Strong analytical and problem-solving skills with the ability to work autonomously on complex technical challenges required
• Good written and verbal communication skills, with the ability to present technical findings to both technical and non-technical audiences required