AI System Engineer at Snapp

General Trias, Cavite, Philippines -

Full Time

Start Date

Immediate

Expiry Date

27 Mar, 26

Salary

0.0

Posted On

27 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Statistics, Data Analysis, Python, ML Frameworks, SQL, Data Preprocessing, Feature Engineering, Model Training, Model Validation, Model Deployment, NLP, Computer Vision, A/B Testing, Problem Solving, Communication, Collaboration

Industry

technology;Information and Internet

Description

Our Journey So Far At Snapp, we’re redefining how cities move. Our ride-hailing and mobility platform connects millions of riders and drivers every day, delivering safe, reliable, and efficient transport solutions. Powered by real-time data and robust infrastructure, we make urban travel faster, simpler, and more sustainable. We operate with the mindset of a global tech leader and the agility of a startup, building services that scale across markets while staying responsive to local needs. Your Impact As an AI System Engineer you will own the end-to-end design, prototyping, deployment and continuous improvement of ML systems that power multiple Snapp verticals. s. You will identify and scope opportunities, shape priorities, recommend solutions, design experiments, and measure impact. You will bring a quantitative mindset to decision-making in partnership with product, business, and operations stakeholders throughout the organization. What You’ll Drive Forward Creation and development of models using AI/ML technologies, including the installation and monitoring of production performance. Partner with business units and cross-functional teams to understand business requirements and integrate additional data needed for creating advanced models. Collaborate closely with engineers to deploy models in production, both in real-time and batch processes, and systematically track and optimize model performance. Act as a subject matter expert on machine learning and predictive modeling, providing guidance and insights. Drive technical innovation through active research and the application of new theories, techniques, and technologies. Mentor junior data scientists, providing guidance, support, and monitoring project progress. Communicate non-technical reports detailing project outcomes and insights to stakeholders. Formulate and oversee data-driven projects to advance business objectives, ensuring alignment with organizational goals. Develop structured frameworks, scalable tools, and organizational processes to enhance company planning and product performance. Design and analyze experiments, communicate results, and make launch decisions. Establish metrics to measure the health of products and the rider and driver experience. What Powers Your Drive Strong foundation in machine learning, statistics, and data analysis. 3+ years of experience as a Data Scientist or in a similar role, with a track record of increasing responsibility and ownership. Proficiency in Python and experience with key ML frameworks (e.g., Scikit-learn, PyTorch, TensorFlow). Solid SQL skills and experience working with both relational and non-relational databases. Deep understanding of the ML model lifecycle: from data preprocessing and feature engineering to model training, validation, deployment, and maintenance. Familiarity with cutting-edge AI techniques, including Retrieval-Augmented Generation (RAG), autonomous agents, and vision-language models (VLMs). Hands-on experience with modern ML/AI development tools and platforms (e.g., LangChain, LlamaIndex, Hugging Face). Ability to work across diverse ML contexts including NLP, computer vision, and tabular data. Practical experience in experimentation, A/B testing, and statistical evaluation. Strong problem-solving skills, with the ability to break down complex issues and deliver actionable insights. Effective communication and collaboration skills — able to explain complex ideas to both technical and non-technical audiences. Highly organized and self-driven; capable of managing multiple priorities and contributing in a team-oriented environment. Nice to have experience in data-centric AI, weak supervision, or noisy label handling. Nice to be familiar with vector databases (e.g., FAISS, chromaDb, Qdrant,..). Nice to have exposure to MLOps tools and workflows (e.g., MLflow, DVC, Airflow). Nice to have Contributions to open-source projects or involvement in applied ML research. Ready to Get on Board? Help us shape the future of ride-hailing and urban mobility. Submit your CV and let’s build smarter cities together.

Responsibilities

As an AI System Engineer, you will design, prototype, deploy, and continuously improve ML systems for Snapp. You will collaborate with various stakeholders to identify opportunities and measure the impact of your solutions.