Job Title: Sr. Machine Learning / AI Engineer / Sr. Data Scientist
Location: Sunnyvale, CA (Onsite) - Candidates should be based in US only
Job Type: Full-time (With benefits)
Mandatory Skills: Generative AI, Azure/GCP
Minimum experience should not be less than 8 years in a related field.
NOTE: DATA ANALYSTS & SOFTWARE DEVELOPERS WILL NOT WORK HERE.
Minimum Education should be Master’s Degree or PhD.
Roles and Responsibilities:
- Platform Design & Architecture: Lead the design and development of a robust, scalable Generative AI Image Platform optimized for ecommerce, personalization, and recommendation use cases. Ensure the platform is multi-tenant and cloud-native, supporting a broad range of business needs.
- Scalability & Performance: Architect the platform to handle millions of real-time requests with low latency and high availability. Implement best practices for high performance and reliability in a cloud environment.
- Generative AI Models: Drive the development and integration of generative models (e.g., GANs, diffusion models) tailored for ecommerce and personalized content generation.
- SaaS Development: Oversee the full lifecycle of a SaaS platform, ensuring modular design, secure multi-tenancy, and smooth onboarding for diverse clients across the personalization and recommendation domains.
- Cross-functional Collaboration: Work closely with product managers, data scientists, and engineers to translate business requirements into technical solutions, driving innovation in personalized image creation and ecommerce experiences.
- Data Analysis & Insights: Leverage advanced data analysis to extract insights from platform usage, model performance, and customer behavior. Use this data to inform model improvements, feature development, and overall platform enhancements.
- Cloud Infrastructure: Design cloud-native solutions leveraging technologies such as Kubernetes, microservices, and serverless architecture to enable seamless scaling and cost efficiency.
What you'll bring:
- Master’s or PhD in Computer Science, Machine Learning, or related field.
- 8+ years of experience in designing and deploying large-scale machine learning systems, with at least 2 years focused on generative AI and cloud-native platforms.
- Deep expertise in building SaaS solutions, including multi-tenant architectures, API design, and security best practices.
- Proven experience in scaling platforms to handle millions of requests, with strong knowledge of distributed systems, cloud infrastructure, and high availability patterns.
- Strong proficiency in generative AI techniques (GANs, diffusion models) and their application in personalization and recommendation systems.
- Experience with cloud platforms (GCP, Azure), container orchestration (Kubernetes), and microservices architecture.