Data/AI Engineer (IoT sphere)

Company Background

The customer offers access solutions and products around the world. Their innovative offerings and partnerships, supported by a smart ecosystem, empower their clients with cutting-edge access solutions, ensuring safe traversal across homes, garages, community spaces, commercial areas, and storage units.

Project Description

The project focuses on strengthening the AI foundation, enhancing validation scripts, and resolving inconsistencies in object detection models across various hardware platforms. Key efforts include improving validation tools for Gen AI-based models, particularly for smart search and descriptive notifications, updating accuracy metrics for people and face detection, and developing automation for model testing on target devices. In parallel, the team will refine the data curation process by shifting attention from traditional object detection to Gen AI needs, emphasizing the curation and annotation of customer-submitted videos. These initiatives aim to ensure consistent model performance and more intelligent, context-aware AI capabilities.

Technologies

• AWS
• Azure
• ML Frameworks
• Databricks
• Apache Spark
• .NET Core

What You'll Do

• Design, develop, and validate next-generation AI platforms that support scalable deployment across diverse edge and cloud environments;
• Build and maintain automation scripts for model validation, fine-tuning, and performance evaluation of object detection and generative AI (GenAI) models;
• Implement CI/CD pipelines for ML workflows to ensure seamless integration and reproducibility;
• Automate testing and benchmarking pipelines for deploying models on heterogeneous embedded devices and hardware;
• Investigate and resolve performance discrepancies caused by quantization, hardware-specific constraints, or platform variations;
• Collaborate with data curation teams to enhance annotation quality, consistency, and efficiency for GenAI applications;

Job Requirements

• Solid experience building and maintaining ETL/ELT pipelines;
• Proficient in handling structured/unstructured data, batch and stream processing, and working with data lakes and warehousing solutions;
• Proficient in developing distributed data processing workflows using Apache Spark;
• Strong Python skills. Comfortable writing production-grade code and building APIs/services for ML applications;
• Hands-on experience working with AWS and/or Azure;
• Experience with ML frameworks (TensorFlow, PyTorch) and basic understanding of generative models, transformers, and embeddings;
• Familiarity with vector databases or LLM orchestration tools (e.g. LangChain);
• Experience with labeling workflows, dataset management, annotation tooling, and quality assurance for computer vision or NLP datasets;
• Able to build fault-tolerant pipelines and support large-scale model integration with monitoring and logging;
• Strong proficiency in Python and core Data Science tools (e.g., NumPy, Pandas, Scikit-learn);
• Hands-on experience with MLOps and CI/CD pipelines for machine learning systems;
• Demonstrated knowledge of model validation, performance benchmarking, and computer vision tasks such as object detection;
• Familiarity with model quantization techniques and edge-device deployment best practices;
• Experience working in cross-functional teams and translating business requirements into scalable ML solutions;
• Experience with Databricks is a plus;
• Bachelor's Degree in Computer Science or equivalent;
• Knowledge of English - from Upper-Intermediate; 

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Internal startup incubator;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.