Machine Learning Engineer

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]