Mid. AI Engineer (Computer Vision)

Synapsis; Jakarta Pusat; On-site; IDR 334,800,000 - 613,800,000; Full time

Job summary

Synapsis is seeking an AI Engineer specialist in computer vision and forecasting to develop, deploy, and optimize AI solutions within production systems. You will build scalable ML models, collaborate with cross-functional teams, and drive data-driven decisions across business units.

The role requires hands-on experience with Python, TensorFlow, PyTorch, and OpenCV, along with data preprocessing, feature engineering, and creating reusable pipelines.

Qualifications

• Bachelor's or Diploma in IT/CS or related field.

Responsibilities

• Develop and optimize ML models for forecasting and computer vision tasks.
• Collaborate with data scientists, software engineers, and product managers to understand business requirements.
• Build and maintain scalable AI pipelines for data collection, preprocessing, feature engineering, model training, validation, and deployment.
• Conduct applied research to implement AI methodologies in CV and time-series forecasting.
• Optimize model performance for accuracy, scalability, and production readiness.
• Process and clean diverse datasets to ensure high-quality inputs for robust models.
• Implement ML models using Python and frameworks such as TensorFlow or PyTorch.
• Conduct rigorous testing and evaluation to ensure models perform well in real-world scenarios.
• Integrate AI models with existing software systems, APIs, and databases to enhance product functionality.
• Monitor and improve model performance post-deployment by analyzing feedback and updating models as necessary.

Skills

Python

TensorFlow

PyTorch

OpenCV

NumPy

Pandas

Scikit-learn

Time-Series Forecasting

Computer Vision

MLOps

Education

Bachelor's degree in IT/CS

Diploma 3/4 in IT/CS

Related majors accepted

Tools

TensorFlow

PyTorch

OpenCV

Keras

Scikit-learn

Job description

Role Purpose

Develop, deploy, and optimize AI solutions with a focus on computer vision and forecasting by building scalable machine learning models, integrating them into production systems, and delivering data-driven solutions that address business needs.

Job Description

• Develop and optimize machine learning models for forecasting and computer vision tasks using state-of-the-art algorithms and techniques.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to understand business requirement.
• Build and maintain scalable AI pipelines for data collection, preprocessing, feature engineering, model training, validation, and deployment.
• Conduct applied research to implement and integrate AI methodologies, particularly in computer vision and time-series forecasting.
• Optimize model performance for accuracy, scalability, and production readiness.
• Process and clean diverse datasets to ensure high-quality inputs for robust machine learning models.
• Implement machine learning models using Python and frameworks such as TensorFlow, PyTorch, or similar libraries.
• Conduct rigorous testing and evaluation to ensure models perform well in real-world scenarios.
• Integrate AI models with existing software systems, APIs, and databases to enhance product functionality.
• Monitor and improve model performance post-deployment by analyzing feedback and updating models as necessary.

Job Requirements

• Graduate from Bachelor, Diploma 3, Diploma 4 degree from IT, Computer Science or other related majors.
• Have a minimum 2 years of experience as an AI Engineer with a strong focus on computer vision and/or forecasting (time-series modeling).
• Strong problem-solving and critical thinking skills, with the ability to work effectively in collaborative, cross-functional teams.
• Excellent communication skills to convey technical concepts to both technical and non-technical stakeholders.
• Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar for model development and deployment.
• Solid understanding of machine learning techniques and algorithms, including Computer Vision (e.g., CNNs, YOLO, object detection) and Time-Series Forecasting (e.g., ARIMA, LSTM).
• Familiarity with essential libraries such as NumPy, OpenCV, Pandas, Scikit-learn, and Matplotlib.
• Hands-on experience in data preprocessing, feature engineering, and creating reusable data pipelines.
• Experience in deploying, monitoring, and maintaining machine learning models in production.
• Familiarity with MLOps practices is a plus.