Success Software Services ★ 3.1

Primary Role of Positions

• Machine Learning Engineer work in project groups of the Delivery organization and are responsible for the implementation of software applications.

Job Duties and Responsibilities

• Design, develop, and deploy machine learning based systems for solving ride hailing problems.

• Design, develop, and maintain a scalable and efficient Machine Learning (ML) platform to support model development, training, deployment, and monitoring.

• Work with cross-functional teams, including data scientists, product managers, and software engineers, to build end-to-end ML solutions.

• Implement and optimize real-time model inference pipelines using FastAPI, Flask, TensorFlow Serving, etc.

• Deploy and manage ML models using MLOps tools (Docker, Kubernetes, Airflow, MLflow).

• Ensure efficient and scalable ML model execution on Google Cloud Platform (GCP) or other cloud services.

• Follow best practices in software engineering, including unit testing, version control (Git), and CI/CD workflows.

• Passionate about learning and sharing knowledge on new technologies.

Required Qualifications

• 2+ years of experience in Machine Learning with a proven track record of deploying ML models to production.

• Strong foundation in Computer Science (data structures, algorithms, system design), Machine Learning (model training, evaluation, deployment), and Backend Development (APIs, databases, distributed systems).

• Proficiency in Python (NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch, Polars, etc.).

• Experience working with SQL for data manipulation and analysis.

• Knowledge of MLOps and cloud platforms (GCP preferred, AWS, or Azure).

• Experience with monitoring and logging tools (Prometheus, Grafana, CloudWatch).

• Familiarity with Kafka, Google Pub/Sub, or similar messaging systems.

• Good in English communication.

• Communication: Ability to explain complex ML concepts to non-technical stakeholders.

• Collaboration: Work effectively with diverse teams across engineering, data science, and product management.

• Problem-solving: Break down complex challenges and apply the right ML techniques to solve them efficiently.

• Experience optimizing model inference (quantization, pruning) – (Nice to Have)

Benefits:

• 13th month salary.

• Quarterly project bonus.

• Referral bonus (up to 30M).

• English incentive - TOEIC 750 (1M/month), TOEIC 900 (2M/month).

• Japanese incentive – N2 (1M/month), N1 (2M/month).

• Technical certificate bonus.

• Opportunities for onsite working (Singapore, Canada, USA, Australia).

• 24/7 insurance for employees working more than 1 year.

• Salary review once a year.

• Annual company trip, teambuilding.

• 12 days leave + 1 birthday leave.

• Internal activities such as excellent employee of quarter or year, Mid-Autumn Festival, Christmas,