Lead AI/ML Engineer (iot Sphere)

Lead AI/ML Engineer (IoT Sphere)

The client is a global leader in smart access solutions, recognized for its top-tier brands found in millions of homes, businesses, and communities worldwide. As a key player in the Smart Home industry, the company operates one of the largest IoT install bases, offering a range of connected devices such as cameras, locks, garage door openers, and gate systems—all powered by their myQ digital ecosystem. Their mission is to create seamless, secure, and intelligent access experiences.

Project Description

The project focuses on enhancing the company's AI infrastructure to support intelligent automation and smarter decision-making across their smart access ecosystem. Key goals include improving validation scripts for generative AI models, developing an automated model testing system for hardware platforms, addressing object detection discrepancies, and updating the data curation process for new generative models. The team will also build and maintain a conversational AI chatbot and an AI-powered Scheduling Assistant for their MyQ Business software. You'll collaborate with cross-functional teams including ML engineers, firmware specialists, and frontend developers.

Technologies

• Python
• SQL
• Apache Spark
• Databricks
• TensorFlow
• PyTorch
• LangChain
• LangGraph
• OpenAI
• FastAPI
• React
• AWS
• Azure
• Docker
• Kubernetes
• Vector Databases (e.g., Pinecone, Weaviate, Qdrant)
• MLflow
• Ray
• DVC
• W&B
• TensorBoard
• Prometheus
• Grafana
• ELK Stack
• Git
• CI/CD tools

What You'll Do

• Build and maintain the AI-powered Scheduling Assistant integrated with email systems and MyQ Business software
• Collaborate closely with frontend engineers to deliver intuitive user interfaces for ML-driven features
• Automate and optimize data ingestion, transformation, and visualization pipelines
• Develop and improve validation scripts for object detection and generative AI models
• Integrate ML components with UI layers and backend services
• Enhance and monitor the performance of large-scale AI models deployed on diverse hardware
• Design fault-tolerant workflows and optimize system performance through observability tools
• Contribute to the development of a conversational data insights chatbot using NLQ tools like Databricks Genie (or similar)

Job Requirements

• 5+ years of experience in machine learning engineering or applied data science
• Strong proficiency in Python and SQL; experience developing production-grade APIs (e.g., FastAPI)
• Hands-on experience with ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS and/or Azure)
• Familiarity with vector databases and orchestration tools such as LangChain or LangGraph
• Proficiency in building distributed data processing workflows using Apache Spark or Databricks
• Experience developing and integrating ML components into full-stack systems
• Knowledge of ML observability tools such as MLflow, W&B, Prometheus, or TensorBoard
• Solid foundation in applied ML, especially in NLP, transformers, embeddings, and GenAI
• Familiarity with Docker; Kubernetes is a plus
• Basic experience with frontend technologies like React is a plus
• Experience with Databricks Genie or similar natural language querying tools is a major plus
• English level: B1+

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.