Senior ML Engineer: Production‑Ready ML & MLOps

Syncron AB; Hinoba-an; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

Syncron AB in the Philippines is seeking a practical, hands-on ML practitioner who can bridge data science and engineering. You will explore data, build models, evaluate performance, write clean production-ready code, and collaborate with MLOps and engineering teams to move models into production.

You should handle data science and ML engineering tasks across model development, deployment, monitoring, and lifecycle management, with GenAI / LLMOps considered nice to have.

Qualifications

• 4–8 years of experience in Data Science, ML Engineering, Applied ML, or related roles.
• Strong hands-on experience with Python & SQL.
• Strong understanding of machine learning algorithms, model evaluation, feature engineering, and validation.
• Experience converting notebooks into reusable, production-quality code.
• Experience with orchestration tools such as Airflow, Kubernetes, Mage, or similar.
• Experience with model lifecycle tools such as MLflow, SageMaker, Azure ML, Vertex AI, or similar.
• Strong understanding of batch inference, model deployment, production ML workflows, and monitoring.
• Experience with Docker, Git, environment management, and CI/CD automation using tools such as GitHub Actions/workflows.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with production ML monitoring concepts such as model/data drift, data quality validation, prediction monitoring, and common failure modes in deployed ML systems.
• Familiarity with NLP fundamentals such as text preprocessing, tokenization, lemmatization, stemming, text representation, and semantic embeddings for search, similarity, classification, and retrieval use cases.
• Ability to analyze model performance across segments, tenants, time periods, and business outcomes.

Responsibilities

• Data Science & Model Development: Understand business problems, perform EDA, feature discovery, target definition, and build/validate ML models across tasks.
• ML Engineering & Productization: Build reusable ML pipelines, production-ready workflows, and multi-tenant config-driven pipelines.
• Model Lifecycle & Release Management: Track experiments, manage model registry/versioning, lineage, metadata, and controlled rollout.

Skills

Python

SQL

ML algorithms

Notebook-to-production

Airflow

Kubernetes

CI/CD

Docker

Git

AWS

Azure

GCP

NLP fundamentals

Model monitoring

Tools

MLflow

SageMaker

Azure ML

Vertex AI

Airflow

Kubernetes

Mage

GitHub Actions

Job description

Syncron AB in the Philippines is seeking a practical, hands-on ML practitioner who can bridge data science and engineering. You will explore data, build models, evaluate performance, write clean production-ready code, and collaborate with MLOps and engineering teams to move models into production.

You should handle data science and ML engineering tasks across model development, deployment, monitoring, and lifecycle management, with GenAI / LLMOps considered nice to have.