Description

Required Qualifications:

• 3+ years in customer-facing AI/ML or infrastructure roles (Field Engineer, Applied AI Engineer, Solutions Architect, ML Engineer, or similar) with a track record of owning technical workstreams in enterprise accounts.
• Shipped real AI/ML production code into customer environments — not just slide decks or advisory engagements.
• Hands-on experience with LLM inference and/or training using open-model frameworks (for example, modern serving stacks and fine-tuning workflows such as SFT; exposure to more advanced approaches like DPO or RFT is a strong plus).
• Strong Python, plus comfort with GPUs and cloud infrastructure (AWS, Azure, or GCP) and container/orchestration tools such as Kubernetes.
• Demonstrated executive-level presence: you can dive deep with an engineer and explain trade-offs to senior leadership in the same day

Key Skills

Education

Any Gradute