300 Machine Learning Engineer jobs in the Philippines

What You'll Do

Domain‑Driven Model Development

• Lead end‑to‑end ML projects (predictive maintenance, golden‑batch optimization, fault‑detection) in manufacturing, energy, water and building contexts.

Data Engineering & Feature Work

• Ingest and preprocess time‑series sensor, PLC, and historian data.
• Engineer features for equipment health, process stability ("golden batch" profiles), energy/water efficiency.

Modeling & Deployment

• Build and validate models (classification/regression) using scikit‑learn, TensorFlow/PyTorch.
• Containerize and serve via TensorFlow Serving, ONNX Runtime or equivalent. Monitor model drift and retrain pipelines in production.

Cross‑Functional Collaboration

• Design and document APIs, message‑queue integrations (Kafka/RabbitMQ) for downstream apps.

Must‑Have Qualifications

Deep Industry Experience

• 3+ years in Manufacturing or relevant roles in Energy, Water or Building Automation.
• Hands‑on understanding of shop‑floor processes, PLC data, preventive vs. predictive maintenance.

ML Fundamentals

• Solid grasp of backpropagation, F1‑score vs. confusion‑matrix trade‑offs, over/under‑sampling.

Software & Data Skills

• Python: threading, async, type‑hints; familiar with pandas, NumPy.
• SQL: complex JOINs, GROUP BY, window functions.
• APIs & Queues: REST/gRPC design, Kafka or RabbitMQ.·

Deployment Frameworks

Experience with TensorFlow Serving or ONNX Runtime on Kubernetes or edge‑devices.

Bonus

• Computer Vision: OpenCV, image‑processing pipelines for visual inspection.
• Edge AI: Raspberry Pi, Jetson Nano or similar—optimizing models for constrained hardware.

What We're Looking For

• Domain‑First Mindset: You know that real impact comes from marrying hands‑on equipment knowledge with ML, not just toy datasets.
• Fast Learner: You'll upskill on new algorithms and tools via online courses and documentation—nothing holds you back.
• Collaborative Communicator: You can translate between data science jargon and operations speak.
• Product‑Obsessed: You see every ML experiment as a step toward a tangible solution for our clients.

Job Types: Full-time, Permanent

Benefits:

• Company Christmas gift
• Company events
• Flexible schedule
• Flextime
• Health insurance
• Life insurance
• Paid training
• Promotion to permanent employee

Work Location: In person

Position Title: Machine Learning Engineer

Salary: Open for discussion/negotiation

Mandatory Qualifications:

• Master's degree in Computer Science, Data Science, Machine Learning, or a related field. Ph.D. is a plus.
• 5+ years of experience in machine learning, data science, or a related field.
• Strong proficiency in programming languages such as Python, R, or Java.
• Extensive experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, etc.
• Proven track record of designing and deploying machine learning models in a production environment.
• Solid understanding of statistical methods, data analysis, and data preprocessing techniques.
• Experience with big data technologies and tools such as Hadoop, Spark, or similar.
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Excellent problem-solving skills and the ability to think critically and creatively.
• Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.
• Experience with natural language processing (NLP), computer vision, or other specialized areas of machine learning is a plus.

Desired Qualifications:

- Experience in Financial institution or Fintech company data analytics

- Publications or contributions to the machine learning community or production experience of product launch.

- Experience with ML Ops practices and tools.

Job Types: Full-time, Permanent

Work Location: In person

Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.

Why ERNI is the Perfect Place for You:

• International Exposure: Work with global clients on cutting-edge projects.
• Inclusive Culture: Thrive in a collaborative and diverse work environment.
• Career Development: Enjoy continuous learning and professional growth opportunities.

Perks and Benefits:

• Career Stability: Enjoy a stable career path with ample project opportunities.
• Immediate Coverage: Private HMO and insurance benefits from day one.
• Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites.
• Comprehensive Benefits: Government-mandated benefits including 13th-month pay.
• Skill Enhancement: Access free training and certifications.
• Wedding Gift: To celebrate your special day.
• Baby Basket: To welcome your newborn to the ERNI family.
• Fruit Basket: Boost of vitamins during hospitalization.
• Office Perks: Enjoy free snacks and coffee.

Growth and Opportunities:

• Free Training: Advance your skills through technical and non-technical training.
• Challenging Projects: Engage in complex software projects across MedTech, Industry,

Finance, and Transportation.

• Supportive Environment: Benefit from a team dedicated to guiding and supporting your success.
• Recognition and Advancement: Receive acknowledgment for your efforts and

opportunities for promotion.

• Open Communication: Experience transparency and value your input in our culture.

Flexibility:

• Hybrid Work Setup: Balance remote and in-person work for better work-life integration.

Events:

• Connect and Celebrate: Participate in a variety of events including leisure, summer,

family, social, and year-end gatherings.

What are our wishes:

We are seeking a hands-on MLOps / Machine Learning Engineer with deep expertise in the Azure Databricks ecosystem to help build our AI/ML platform from the ground up. You will work collaboratively with a cross-functional team to implement a predefined architecture and establish the foundations of a production-grade system that adheres to strict data governance and compliance standards.

Because this is a greenfield build, the role combines MLOps and Machine Learning engineering responsibilities into a single, integrated position. You will contribute across the end-to-end ML lifecycle from data pipelines and governance through to model deployment and monitoring with a strong focus on collaboration. As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable

• 5+ years of experience as an ML Engineer, MLOps Engineer, or similar hybrid role.
• Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Proven expertise in Azure Databricks, Azure ML, Data Factory, Delta Lake, and MLflow.
• Hands-on experience with Git for pipeline development (branching strategies, code reviews, version control best practices).
• Solid understanding of MLOps practices, CI/CD, and production ML requirements.
• Experience working under strict governance and compliance frameworks.
• Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or related field.

Preferred Qualifications

• Familiarity with Generative AI, LLM deployment, or RAG pipelines using Azure OpenAI Service, LangChain, or open-source LLMs.
• Experience with vector databases (e.g., FAISS, Milvus, Pinecone) and model explainability tools.
• Azure certifications (e.g., Azure Data Scientist Associate, Azure Solutions Architect, or Azure DevOps Engineer).

Soft Skills

• Curious and eager to learn — passionate about exploring new technologies and approaches.
• Collaborative mindset — thrives in a team environment and values collective success.
• Adaptable — comfortable in a role that spans both ML engineering and MLOps, with evolving responsibilities.
• Problem-solving skills — able to balance compliance requirements with practical implementation.
• Attention to detail — especially in governance, testing, and documentation.
• Proactive communicator — ensures alignment with teammates and stakeholders.

How can you contribute to the team?

Platform & Pipeline Development

• Collaborate with the team to implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
• Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
• Ensure version control and collaboration through Git-based workflows.

Model Lifecycle & MLOps

• Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.
• Define and manage model registries, versioning, and traceability.

Data Governance & Compliance

• Implement strict controls for data access, lineage, and security.
• Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
• Embed compliance requirements into system design from day one.

Deployment & Monitoring

• Deploy models for real-time and batch inference using MLflow
• Contribute to monitoring frameworks for drift detection, latency, and performance degradation using Azure Monitor or equivalent.

CI/CD & Infrastructure

• Integrate pipelines with Azure DevOps or GitHub Actions for automated testing, validation, and deployment.
• Support infrastructure-as-code with Terraform, Bicep, or ARM templates to ensure reproducibility and scalability.

Collaboration & Documentation

• Partner with data scientists to productionize research prototypes.

• Document workflows, governance processes, and best practices for ongoing maintainability.

Switzerland · Germany · Spain · Slovakia · Romania · Philippines · Singapore · USA

ERNI Development Center Philippines Inc., 9th Floor, Lica Malls Shaw, 500 Shaw Boulevard, 1555, Mandaluyong City, Philippines

| |

About Us

We're a fast-moving startup on a mission to revolutionize the call centre industry using the power of AI and Large Language Models. We're building intelligent systemsto enhance customer experience, supercharge agent performance, and drive operational excellence.

Through advanced conversational AI, we build systems that understand, adapt, and evolve with every conversation. Our platform powers decision-support tools and intelligent virtual agents helping call centers deliver faster, smarter, and more human customer service—where every interaction matters.

As an ML Engineer, you'll design, train, and deploy models that not only empower better decisions and agent experiences—but also power the core intelligence behind real-time conversations. If you're a self-starter with a passion for deploying ML at scale and know how to get your hands dirty with LLMs, we want you on our founding team.

What You'll Do

• Design, build, and deploy ML pipelines and LLM-powered applications from scratch.
• Fine-tune, prompt, and integrate state-of-the-art LLMs (e.g., OpenAI, LLaMA, Mistral).
• Apply advanced techniques like retrieval-augmented generation (RAG), tool use, and embedding search.
• Collaborate with product and engineering to build AI-driven features for real-world call centre use cases (e.g., agent coaching, auto summarization, sentiment analysis).
• Own experiments end-to-end — from hypothesis to deployment — with minimal supervision.
• Optimize model inference (latency, memory) for production-scale workloads.
• Set up scalable infrastructure for model training, evaluation, and continuous improvement.
• Help shape our ML/AI roadmap and contribute to technical strategy.

What We're Looking For

• 3+ years of experience as an ML Engineer
• Deep expertise in NLP and LLMs (e.g., transformers, LoRA, vector search, prompt engineering).
• Strong Python skills and hands-on experience with frameworks like Hugging Face Transformers, LangChain, OpenAI, PyTorch.
• Experience deploying ML models in production (e.g., APIs, containers, cloud-based services).
• Comfort working in early-stage/startup environments — fast pace, lots of ambiguity, high impact.
• Ability to work autonomously and make product-informed decisions with minimal oversight.

Bonus Points For

• Experience in or knowledge of the call centre / contact centre space.
• Familiarity with voice-to-text models, real-time analytics, or conversation intelligence.
• MLOps experience (e.g., model versioning, monitoring, CI/CD).
• Prior experience with vector databases (e.g., FAISS, Pinecone, Weaviate).

Why Join Us?

• Be part of a mission-driven startup from the ground up.
• Shape the future of AI in a high-impact, real-world industry.
• Work remotely with flexibility and autonomy.
• Competitive compensation

Job Type: Full-time

Work Location: Remote

ADEC Innovation
 is a global, purpose-driven business solutions organization that specializes in integrating business process solutions with sustainability and environmental management. With a history spanning over three decades, the company was founded in Manila, Philippines, in 1996 and has since expanded its footprint to six continents with a workforce of over 5,000 associates. ADEC Innovation is driven by a mission to advance sustainable business and operational practices by transforming information into knowledge and reshaping risk into positive impact and value for its clients.

We are looking for 
OCR Processor (Machine Learning)
 to join our growing team

Basic Qualification:

• Graduate of BS in Computer Science, Information Technology, or any related related field
• Must have at least 1 year of work experience in a relevant or related role/capacity; experience with OCR technologies and machine learning-driven data extraction is considered an advantage
• Must be amenable to work onsite in Alabang, Muntinlupa on a shifting schedule

Duties and Responsibilities:

Processing:

• Review and upload vendor files into the OCR software to generate output files for daily uploads into Expense Logic.
• Identify and report EL Mapping or Customer Mapping issues to the IT team. Address OCR software-related issues with the team on a daily basis.
• Maintain a daily log of processed invoices, issues encountered, and monthly averages; report findings to leadership.

Integration with Applications:

• Integrate OCR solutions with existing systems to automate data extraction workflows.
• Collaborate with software developers to ensure smooth and efficient integration of OCR functionalities.

Training and Testing:

• Tag and train the OCR model using machine learning techniques to improve recognition accuracy.
• Conduct thorough testing and validation of OCR files to ensure high precision and recall rates.

Customization and Configuration:

• Customize OCR solutions to meet specific project requirements and support various document formats.
• Configure OCR parameters for optimal performance across different use cases.

Performance Optimization:

• Enhance OCR performance, scalability, and resource efficiency.
• Implement parallel processing and other optimization techniques to improve processing speed.

Documentation:

• Create and maintain detailed documentation for OCR algorithms, configurations, and integration procedures.
• Provide clear documentation for troubleshooting and support purposes.

What's in it for you?

• Competitive salary package
• Life Insurance on Day 1
• HMO with free dependent*
• Paid leave credits*

Founded in 1994 and headquartered in Switzerland, ERNI is a leading Software Development company with over 800 employees worldwide. Specializing in IT and software engineering, we drive innovation in process and technology. Our first service center in Asia Pacific, located in Metro Manila (Mandaluyong), supports clients across Europe, APAC, the Philippines, and the USA. As we continue to grow, we're looking for passionate and motivated individuals to join our team.

Why ERNI is the Perfect Place for You:

• International Exposure: Work with global clients on cutting-edge projects.
• Inclusive Culture: Thrive in a collaborative and diverse work environment.
• Career Development: Enjoy continuous learning and professional growth opportunities.

Perks and Benefits:

• Career Stability: Enjoy a stable career path with ample project opportunities.
• Immediate Coverage: Private HMO and insurance benefits from day one.
• Jubilee Celebration: A 5-year milestone includes a complimentary trip to any European ERNI sites.
• Comprehensive Benefits: Government-mandated benefits including 13th-month pay.
• Skill Enhancement: Access free training and certifications.
• Wedding Gift: To celebrate your special day.
• Baby Basket: To welcome your newborn to the ERNI family.
• Fruit Basket: Boost of vitamins during hospitalization.
• Office Perks: Enjoy free snacks and coffee.

Growth and Opportunities:

• Free Training: Advance your skills through technical and non-technical training.
• Challenging Projects: Engage in complex software projects across MedTech, Industry,

Finance, and Transportation.

• Supportive Environment: Benefit from a team dedicated to guiding and supporting your success.
• Recognition and Advancement: Receive acknowledgment for your efforts and

opportunities for promotion.

• Open Communication: Experience transparency and value your input in our culture.

• Flexibility:

• Hybrid Work Setup: Balance remote and in-person work for better work-life integration.

Events:

• Connect and Celebrate: Participate in a variety of events including leisure, summer,

family, social, and year-end gatherings.

What are our wishes:

We are seeking a hands-on MLOps / Machine Learning Engineer with deep expertise in the Azure Databricks ecosystem to help build our AI/ML platform from the ground up. You will work collaboratively with a cross-functional team to implement a predefined architecture and establish the foundations of a production-grade system that adheres to strict data governance and compliance standards.

Because this is a greenfield build, the role combines MLOps and Machine Learning engineering responsibilities into a single, integrated position. You will contribute across the end-to-end ML lifecycle from data pipelines and governance through to model deployment and monitoring with a strong focus on collaboration. As the platform grows, you will help shape best practices and define clear processes, ensuring responsibilities remain focused and sustainable

• 5+ years of experience as an ML Engineer, MLOps Engineer, or similar hybrid role.
• Strong proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Proven expertise in Azure Databricks, Azure ML, Data Factory, Delta Lake, and MLflow.
• Hands-on experience with Git for pipeline development (branching strategies, code reviews, version control best practices).
• Solid understanding of MLOps practices, CI/CD, and production ML requirements.
• Experience working under strict governance and compliance frameworks.
• Bachelor's or Master's degree in Computer Science, Machine Learning, Engineering, or related field.

Preferred Qualifications

• Familiarity with Generative AI, LLM deployment, or RAG pipelines using Azure OpenAI Service, LangChain, or open-source LLMs.
• Experience with vector databases (e.g., FAISS, Milvus, Pinecone) and model explainability tools.
• Azure certifications (e.g., Azure Data Scientist Associate, Azure Solutions Architect, or Azure DevOps Engineer).

Soft Skills

• Curious and eager to learn — passionate about exploring new technologies and approaches.
• Collaborative mindset — thrives in a team environment and values collective success.
• Adaptable — comfortable in a role that spans both ML engineering and MLOps, with evolving responsibilities.
• Problem-solving skills — able to balance compliance requirements with practical implementation.
• Attention to detail — especially in governance, testing, and documentation.
• Proactive communicator — ensures alignment with teammates and stakeholders.

How can you contribute to the team?

Platform & Pipeline Development

• Collaborate with the team to implement the initial AI/ML architecture on Azure Databricks, setting up infrastructure and workflows.
• Design and build scalable, reproducible ML pipelines for data ingestion, feature engineering, training, testing, and deployment.
• Ensure version control and collaboration through Git-based workflows.

Model Lifecycle & MLOps

• Establish processes for automated model training, tuning, deployment, and monitoring using Databricks MLflow and Azure ML Pipelines.
• Define and manage model registries, versioning, and traceability.

Data Governance & Compliance

• Implement strict controls for data access, lineage, and security.
• Ensure all pipelines and models comply with regulatory requirements, auditability, and ML ethics standards.
• Embed compliance requirements into system design from day one.

Deployment & Monitoring

• Deploy models for real-time and batch inference using MLflow
• Contribute to monitoring frameworks for drift detection, latency, and performance degradation using Azure Monitor or equivalent.

CI/CD & Infrastructure

• Integrate pipelines with Azure DevOps or GitHub Actions for automated testing, validation, and deployment.
• Support infrastructure-as-code with Terraform, Bicep, or ARM templates to ensure reproducibility and scalability.

Collaboration & Documentation

• Partner with data scientists to productionize research prototypes.

• Document workflows, governance processes, and best practices for ongoing maintainability.

Switzerland · Germany · Spain · Slovakia · Romania · Philippines · Singapore · USA

ERNI Development Center Philippines Inc., 9th Floor, Lica Malls Shaw, 500 Shaw Boulevard, 1555, Mandaluyong City, Philippines

| | (email protected)

Gratitude Philippines is hiring a Full time Machine Learning Engineer role in Mandaluyong, NCR. Apply now to be part of our team.

Job summary:

• Flexible hours available

Machine Learning Developer

We are looking for a skilled Machine Learning Developer to join our team. In this role, you'll be tasked with designing and implementing machine learning models to solve complex problems and enhance our applications' capabilities. You will work closely with data scientists and software developers to integrate AI functionalities seamlessly.

Responsibilities:

• Designing and developing machine learning and deep learning systems.
• Running machine learning tests and experiments to enhance model accuracy.
• Implementing appropriate ML algorithms to solve various tasks and improve application performance.
• Collaborating with data engineers to build data and model pipelines.
• Analyzing and visualizing data to drive insights and optimize performance.
• Staying updated with the latest machine learning technologies and methodologies.
• Ensuring that algorithms generate scalable and efficient solutions.

Requirements:

• Strong proficiency in Python (proficiency in C# and .NET is preferred).
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
• Knowledge of data structures, data modeling, and software architecture.
• Familiarity with cloud services (Azure, AWS, or Google Cloud) and their machine-learning tools is preferred.
• Ability to work with large data sets and understand complex algorithms.
• Strong analytical and problem-solving skills.
• Excellent English oral and written communication skills.
• Willingness to work on Pacific Standard Time (8:00 AM – 5:00 PM California Time).
• Must own a Laptop or Desktop (8GB RAM, Core i5 or above) with an internet connection of at least 10mbps.

Mandatory Qualifications

• Master's degree in Computer Science, Data Science, Machine Learning, or related field (Ph.D. is a plus).
• 5+ years of experience in machine learning, data science, or related field.
• Strong programming skills in Python, R, or Java.
• Extensive experience with ML frameworks: TensorFlow, PyTorch, scikit-learn, etc.
• Proven track record of designing and deploying ML models in production.
• Solid understanding of statistical methods, data analysis, and preprocessing techniques.
• Experience with big data tools (Hadoop, Spark, etc.).
• Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Excellent problem-solving, critical thinking, and communication skills.
• Experience in NLP, computer vision, or specialized ML domains is a plus.

Desired Qualifications

• Experience in financial institutions or fintech data analytics.
• Publications, open-source contributions, or participation in the ML research community.
• Experience with ML Ops practices and tools for scalable deployment and monitoring.

Job Types: Full-time, Permanent

Work Location: In person