Lead Machine Learning Cloud Architect

Key Skills

Aartificial intelligence, Algorithms, Apache Cassandra, Apache Hive, API, Big Data Technology, C++, Computer Vision (CV), Deep Learning, DevOps, Google Cloud Platform (GCP), Lakehouse, Leadership Skill, Machine learning techniques, MLOps tools, Python Programming, PyTorch, RESTful, Scikit-learn, TensorFlow

Job Description

Would you like to join a small, driven and growing team where you can leverage your data science/machine learning/MLOps/DevOps experience to build highly impactful AI/CV solutions? If so, we have an exciting opportunity for you to join our team. 

You will be hands-on in leading machine learning cloud architecture and its implementation within the CTO team of Zebra Technologies. You will be responsible for collaborating with project teams, ensuring the solution architecture creates delightful experiences for internal and external stakeholders!

Responsibilities:

• Have a significant role in establishing ML strategy and architecture. 
• Design and implement robust, scalable, and highly available cloud-based solutions. 
• Effectively communicate with and influence key stakeholders across the enterprise, at all levels of organizations. 
• Be part of a high performing team developing and implementing AI/CV algorithms to solve complex problems and create unique solutions in retail, manufacturing, transport and logistics and healthcare. 
• Optimize ML/AI delivery processes with cross-functional teams. 
• Identify opportunities and shape use-cases where AI/ML can be applied. 
• Promote ML technologies and patterns. 
• Stay updated on ML advancements and cloud offerings. 
• Guide AI/ML projects from inception to production. 
• Demonstrate expertise in software engineering fundamentals and best practices. 
• Provide technical leadership and mentorship. 
• Facilitate the development and deployment of proof-of-concept machine learning systems. 
• Collaborate with engineers who are producing edge-based solutions to maximize sharing of developed software assets and processes between cloud and edge. 
• Drive standards, procedures, and tools to accelerate ML Engineering projects. 
• Conduct architecture reviews and issue resolution. 
• Work in an agile environment and evaluate pre-project ideas in terms of technical complexity, solution architecture, and estimated effort. 

Qualifications:

• Bachelor's degree in Computer Science, Software, or related field
• Significant experience in architect or software engineering roles
• Proficiency in cloud environments, preferably GCP, with modern techniques/tools
• MLOps experience with deployment and monitoring focus
• Industry expertise in Machine Learning (model development, distributed training, pipeline development, etc.)
• Experience creating scalable platforms for internal/external users
• Architecting Data Science/ML platforms with Enterprise, Big Data, Image, and Time Series data
• Familiarity with RESTful API and event-driven architectures
• Understanding of DevOps and MLOps tool chains, including low-latency ML model deployment
• Proficiency in Python; C++ is a plusHands-on experience deploying ML/DL solutions using modern frameworks (Tensorflow, SNPE, OpenVino, Keras, PyTorch, scikit-learn)

Bonus Skills:

Familiarity with ML ecosystem tools (Hive, Cassandra, Lakehouse, etc.) for Data StorageExpertise in data curation and architecting for ML project support