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Professional Machine Learning Engineer (Azure Databricks)

ERNI PhilippinesMandaluyong, Metro Manila, Philippines

13 days ago

Job description

Overview

ERNI Development Center Philippines Inc., 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\u2019re looking for passionate and motivated individuals to join our team.

Why ERNI

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 looking for a motivated MLOps / Machine Learning Engineer with strong experience in the Azure Databricks ecosystem to support the development of our AI / ML platform. You will work as part of a cross-functional team to build and maintain pipelines, implement MLOps practices, and ensure compliance with data governance standards.

This role is hands-on, focusing on applying best practices in ML engineering and MLOps to deliver reliable, scalable solutions. You will work closely with senior engineers and data scientists to productionize machine learning workflows and continuously improve processes.

Responsibilities

Platform & Pipeline Development : Contribute to building and maintaining ML pipelines for data ingestion, feature engineering, training, testing, and deployment in Azure Databricks.

Model Lifecycle & MLOps : Support model training, tuning, deployment, and monitoring using Databricks MLflow or Azure ML.

Data Governance & Compliance : Apply data security and access control standards as defined by the team.

Deployment & Monitoring : Deploy models for batch and real-time inference under guidance from senior engineers; help implement monitoring for performance and drift detection.

CI / CD & Infrastructure : Contribute to integrating pipelines with CI / CD tools such as Azure DevOps or GitHub Actions; support infrastructure-as-code practices (Terraform, Bicep, or ARM templates).

Collaboration & Documentation : Work closely with data scientists to move prototypes into production; document workflows and contribute to knowledge sharing within the team.

Qualifications

2–4 years of experience as an ML Engineer, MLOps Engineer, or related role.

Solid proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow.

Practical experience with Azure Databricks, MLflow, and Delta Lake.

Familiarity with Git-based workflows and CI / CD pipelines.

Understanding of MLOps principles and production ML requirements.

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.

Preferred Qualifications

Experience with Generative AI, LLM deployment, or RAG pipelines is a plus but not required.

Exposure to Azure ML, Data Factory, and vector databases.

Azure certifications (Data Scientist Associate, Solutions Architect, or DevOps Engineer) are advantageous.

Soft Skills

Eager to learn and grow — curious about new tools and methods.

Collaborative and supportive — enjoys working with cross-functional teams.

Detail-oriented — ensures quality in governance, testing, and documentation.

Strong communicator — able to share progress and challenges effectively.

How can you contribute to the team?

Platform & Pipeline Development

Contribute to building and maintaining ML pipelines for data ingestion, feature engineering, training, testing, and deployment in Azure Databricks.

Collaborate with senior engineers on infrastructure setup and workflow automation.

Follow Git-based workflows for version control and collaboration.

Model Lifecycle & MLOps

Support model training, tuning, deployment, and monitoring using Databricks MLflow or Azure ML.

Contribute to managing model registries, versioning, and traceability.

Data Governance & Compliance

Apply data security and access control standards as defined by the team.

Ensure ML pipelines adhere to compliance and governance frameworks.

Deployment & Monitoring

Deploy models for batch and real-time inference under guidance from senior engineers.

Help implement monitoring for performance and drift detection

CI / CD & Infrastructure

Contribute to integrating pipelines with CI / CD tools such as Azure DevOps or GitHub Actions.

Support infrastructure-as-code practices (Terraform, Bicep, or ARM templates).

Collaboration & Documentation

Work closely with data scientists to move prototypes into production.

Document workflows and contribute to knowledge sharing within the team.

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

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Machine Learning Engineer • Mandaluyong, Metro Manila, Philippines

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