Build and lead a small engineering team, including hiring, onboarding, coaching and developing engineers, setting clear expectations and fostering a culture of ownership, technical excellence and continuous learning.
ML Pipeline Contribution: Package models in Docker; contribute to CI/CD scripts under guidance; run inference tests and support deployment validation in product development environments.
Build and optimize multimodal LLM applications for content generation and understanding, including product copywriting, semantic search recall, and business potential/CTR prediction.
Infrastructure & Performance Optimization: Manage and optimize GPU/accelerator infrastructure (on cloud platforms like AWS, Azure, GCP or on-prem NVIDIA clusters) to support high-performance model training and inference. Drive token efficiency, latency reduction, and cost optimization in AI pipelines (through techniques like model quantization, batching, and caching).
What's needed: 5+ years in a technical problem-solving role with strong software and systems design fundamentals. You should be comfortable scoping ambiguous problems alongside sales, product, or delivery teams, and genuinely enjoy sitting in the room with a customer and driving toward a decision rather than waiting for a polished brief. Experience working across multiple systems, integrations, and data flows is essential, along with real curiosity about making AI agents work reliably in production — not just in a demo.
ML Pipeline Contribution: Package models in Docker; contribute to CI/CD scripts under guidance; run inference tests and support deployment validation in product development environments.
Develop a deep understanding of the business logic and merchant needs within e-commerce vertical domains, enabling Agents to accurately understand and execute highly specialized and complex business requirements, and truly solve real-world problems in merchant operations;
HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.
Evaluate emerging AspenTech capabilities and industry trends (Industry 4.0, MES/MOM convergence, cloud-enabled historians) and advise leadership on adoption strategy.
Partner closely with Product, Design, Security, Blockchain, and Infrastructure leaders to translate business priorities into impactful mobile solutions and seamless user experiences.