AI & Data Science Engineer (Python, LLM, Vision, Audio)

Overview

Galsie is a smart home startup dedicated to streamlining the adoption & configuration of smart home systems through intuitive interfaces, data-driven suggestions, and adaptive assistance.

We're primarily a software company (with hardware as a secondary focus), building an integrated ecosystem of services and tools that work together to deliver a next-level smart home experience. Our core software systems include:

• GCS (Galsie's Cloud Services): Backend cloud platform built in Java for managing homes, devices, users, automations, third-party integrations, and more.
• GDS (Galsie’s Device Stack): A software stack built in C++ that runs directly on Galsie's Smart Devices, enabling seamless integration with other ecosystems and localized home operations.
• GalPyOps: Python-based operations layer handling analytics, machine learning, and AI for both GCS and GDS.
• GalSite: Our main web presence, built using a custom proprietary reactive front-end framework written in TypeScript, HTML, CSS, and Python.
• GalApp: Mobile application for phones, tablets, and wearables. Written in Swift for iOS and Kotlin for Android.

Position

We are currently seeking a Data Scientist with expertise in python development, data analysis, statistics, computer vision, audio processing, machine-learning and AI system development to help design, architect & build Galsie's tracking, recognition, and predictive systems - as well as our LLM-based assistant.

Responsibilities

• Architect, develop, and maintain data pipelines and storage systems optimized for AI model training and inference (structured, unstructured, time-series, and multimedia data).
• Apply advanced data analysis and statistical methods to identify automation opportunities, user preferences, and predict next likely actions, both globally and on a per-user basis.
• Design and implement personalized recommendation engines and predictive models based on user data and smart home events.
• Develop LLM-based agents and workflows that interact with users for intelligent, context-aware suggestions & assistance.
• Build and refine Galsie’s AI systems for object recognition, user identification, and event detection from image, video, and audio footage using tools like OpenCV, TensorFlow, PyTorch, and custom models.
• Research, prototype, and productionize new AI models, algorithms, and architectures that enhance the smart home experience.
• Stay current with AI & ML development trends, and propose technologies or tools that improve efficiency and quality.
• Write clean, well-documented code that meets product requirements
• Maintain and improve CI/CD pipelines, and ensure reliability & responsiveness of the iOS Application.
• Collaborate with cross-functional teams including cloud, mobile, and device teams to integrate AI features throughout Galsie’s ecosystem.

Required Qualifications

• 4+ years of experience in data science, AI, and software development.

• 2+ years hands-on experience with computer vision, image/video processing (OpenCV, TensorFlow, PyTorch, or similar).

• 2+ years experience with audio processing (speech recognition, event detection, classification, etc.).

• Background in data analysis, statistics, and predictive modeling.

• Proven Experience in LLM prompt engineering, fine-tuning, and agent orchestration using frameworks like LangChain, OpenAI APIs, HuggingFace Transformers, or .

• Experience architecting data storage systems for AI pipelines, such as using time-series databases, object storage, and hybrid data lakes.

• Proficiency in designing AI/ML systems with scalability, modularity, and maintainability in mind.

• 3+ years experience Python and relevant data science/ML ecosystems (NumPy, pandas, scikit-learn, TensorFlow, PyTorch).

• Strong understanding of object-oriented and functional programming, clean code practices, and design patterns.

• Proficient with Git, GitHub workflows, and collaborative software development.

• Strong verbal and written skills, and proficiency in English.

Additional Preferred Qualifications

• Experience in smart home, IoT, or edge computing AI systems.
• Experience building and training deep learning models, including LLMs, CNNs, RNNs, and custom architectures.
• Familiarity with device-based AI acceleration frameworks (TensorRT, CoreML, ONNX Runtime, etc.).
• Knowledge of privacy-preserving ML techniques (federated learning, edge AI, etc.).
• Experience in cloud-based AI infrastructure (AWS, Azure ML, GCP AI, or similar).
• Experience with recommendation engines, behavior modeling, and personalization systems.
• Experience with data annotation pipelines and synthetic data generation for training purposes.

Work Hours, Availability, and Compensation

• Position Type: Part-time
• Working Hours: 5 hours per weekday, 3 hours on Saturday
• Office Hours: 9:00 AM – 7:00 PM (Beirut time)
• Work Hour Flexibility: Working hours must be completed within office hours
• Availability: Must be reachable and responsive during office hours to support team members
• Compensation: $400–$800 USD/month, based on experience and performance

Equity & Ownership

• ESOP: You will be granted an Employee Stock Ownership Plan (ESOP), giving you a stake in Galsie’s long-term success.
• Stock Options: You will also receive options to purchase company stock at reduced prices, providing additional opportunity for ownership and future growth participation.

Why join us?

At Galsie, you’ll be part of a forward-thinking, close-knit team solving real-world challenges in the smart home space. You’ll have the opportunity to work on a modern tech stack, influence key architectural decisions, and shape the future of home automation alongside passionate engineers and creators.

We value clean code, thoughtful design, and a willingness to learn and grow. Beyond technical growth, we also believe in shared success — which is why you'll receive equity through our Employee Stock Ownership Plan (ESOP) and stock options at reduced prices, giving you a real stake in what we’re building.

If you're excited by the idea of building the future of smart living and being part of a team where your contributions truly matter, we’d love to hear from you.