Description

You will own technical workstreams for enterprise AI/ML deployments, delivering production-grade solutions directly into customer environments.

This role is on-site.

Responsibilities

• Ship real AI/ML production code, including LLM inference and training workflows, into customer environments.
• Implement modern serving stacks and fine-tuning processes such as SFT, with exposure to DPO or RFT.
• Manage cloud infrastructure and container orchestration using Kubernetes across AWS, Azure, or GCP.
• Communicate technical trade-offs to senior leadership while diving deep into engineering details.

Required Skills

• 3+ years in customer-facing AI/ML or infrastructure roles (Field Engineer, Applied AI Engineer, Solutions Architect, ML Engineer).
• Strong Python programming skills.
• Hands-on experience with LLM inference and training using open-model frameworks.
• Proficiency with GPUs and cloud platforms (AWS, Azure, or GCP).
• Experience with container/orchestration tools, specifically Kubernetes.
• Proven track record of owning technical workstreams in enterprise accounts.

Preferred Skills

• Experience with advanced training approaches like DPO (Direct Preference Optimization) or RFT.
• Executive-level presence and ability to explain complex technical concepts to non-technical stakeholders.

Key Skills

Education

Any Gradute