Professional Machine Learning Engineer

Professional Machine Learning Engineer (Azure Databricks) Location: ERNI Mandaluyong, National Capital Region, Philippines 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. 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. 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. Hybrid Work Setup: Balance remote and in‑person work for better work‑life integration. Events: Participate in a variety of events including leisure, summer, family, social, and year‑end gatherings. Job Overview 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 productionise machine learning workflows and continuously improve processes. Core Responsibilities 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. Support model training, tuning, deployment, and monitoring using Databricks MLflow or Azure ML. Contribute to managing model registries, versioning, and traceability. Apply data security and access control standards as defined by the team. Ensure ML pipelines adhere to compliance and governance frameworks. Deploy models for batch and real‑time inference under guidance from senior engineers. Help implement monitoring for performance and drift detection. Integrate pipelines with CI/CD tools such as Azure DevOps or GitHub Actions. Support infrastructure‑as‑code practices (Terraform, Bicep, or ARM templates). 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. Additional Information Seniority level: Not Applicable Employment type: Full‑time Job function: Engineering and Information Technology Industries: IT Services and IT Consulting #J-18808-Ljbffr