Company Description
PT Kreasi Citra Solusi (KCS) is a trusted partner in building smart technology ecosystems, transforming technological challenges into innovative opportunities. We cater to various sectors including government, manufacturing, education, and telecommunications with well-designed solutions that optimize cost efficiency and competitive advantage. The company is committed to delivering projects on time, within budget, and to the highest quality standards. KCS holds ISO 9001:2015 and ISO 27001:2022 certifications, ensuring our processes are measured, organized, and secure.
Role Description
We are looking for a talented and highly motivated AI Engineer to own the entire machine learning lifecycle from conception to production. This is a unique opportunity to build our AI capabilities from the ground up, working directly with founders and stakeholders to solve our most critical business challenges. You will be responsible for everything from building our data infrastructure and developing predictive models to deploying them as scalable, real-time services.
Key Responsibilities:
- Data Engineering: Design, build, and maintain robust and scalable data pipelines to collect and process data from various sources.
- Data Science & Modeling: Analyze large, complex datasets to extract valuable insights. You will research, design, and train machine learning models to solve problems.
- ML Engineering & Deployment: Deploy machine learning models into a production environment. This includes building APIs, containerizing models, and ensuring they are scalable, reliable, and performant.
- End-to-End Ownership: Manage the entire project lifecycle, from understanding the business requirements and defining success metrics to monitoring and iterating on deployed models.
- Collaboration: Work closely with our product and engineering teams to integrate AI-powered features into core application.
What We&aposre Looking For (Qualifications):
Must-Haves:
- 5+ years of hands-on experience in a data science or AI/ML role with a proven track record of deploying models into production.
- Expert proficiency in Python and its data science libraries (Pandas, NumPy, Scikit-learn).
- Strong experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch).
- Solid understanding of and experience with SQL and relational databases (e.g., PostgreSQL).
- Demonstrated experience building APIs for model serving (e.g., using Flask or FastAPI).
- Hands-on experience with a major cloud platform (AWS, Google Cloud, Azure, Alibaba or BytePlus).
- A self-starter mentality, with the ability to work independently and manage projects with minimal supervision.
Nice-to-Haves:
- Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
- Experience with big data technologies (e.g., Spark).
- Familiarity with MLOps tools and best practices.
- Experience working in a startup environment.
- A Bachelors or Masters degree in related quantitative field.
