AI​/ML Engineer; IoT sphere

Our client is a global leader in smart access solutions, offering top-tier connected products such as cameras, locks, card readers, garage door openers, and gates. With one of the largest IoT install bases worldwide, their innovative ecosystem supports millions of homes and businesses with secure, real-time digital access. The company continues to drive the Smart Home industry forward through AI-powered advancements in video analytics, object detection, and contextual automation.

This AI-driven initiative focuses on improving the client's smart video ecosystem by enhancing the AI foundation, refining validation scripts for generative models, addressing discrepancies in object detection performance, and automating model testing across embedded devices. A major component involves curating and annotating video data to fine-tune models for smart search and descriptive notifications. The long-term objective is to develop intelligent systems capable of summarizing video events and generating context-aware alerts using a combination of computer vision and large language models (LLMs).

• Python
• FastAPI
• Docker
• AWS
• Databricks
• Tensor Flow
• Py Torch
• OpenCV
• Lang Chain
• Lang Graph
• OpenAI (CLIP, GPT-4)
• Qdrant
• Pinecone
• Weaviate
• YOLO
• SAM
• SSD
• MLflow
• DVC
• Ray
• W&B
• Tensor Board
• Grafana
• Label Studio
• Label Img
• CVAT

• Design, develop, and validate smart video search and summarization systems
• Build and optimize ML pipelines for object detection, event tagging, and descriptive alerts
• Collaborate with firmware teams to implement automated model testing on target devices
• Work with video datasets to curate, label, and annotate events for AI training
• Integrate LLMs to contextualize visual events and enable semantic grouping
• Maintain high-quality production-grade code for APIs and ML services
• Partner with product and engineering teams to ship AI-driven features for intelligent notifications
• Implement monitoring, observability, and continuous evaluation for deployed models

• 5+ years of experience in ML/AI engineering
• Strong proficiency in Python and experience with ML frameworks such as Tensor Flow and Py Torch
• Proficient in building distributed workflows using Apache Spark or Databricks
• Hands-on experience in cloud environments (AWS and/or Azure)
• Familiarity with FastAPI, Docker, and CI/CD practices
• Background in computer vision, including object detection and tracking (YOLO, SAM, SSD)
• Experience working with annotation tools (Label Studio, CVAT, etc.) and dataset management
• Understanding of LLMs, transformers, and generative AI techniques; experience with Lang Chain or similar orchestration frameworks
• Proficiency in building scalable, fault-tolerant ML pipelines with monitoring/logging
• Familiarity with event aggregation and generating natural language summaries from video

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;
• 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.

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