Staff GenAI & ML Engineer – Enterprise Solutions (Hybrid)

snorkelai; United States; Hybrid; USD 230,000 - 360,000; Full time

Benefits offered by this job

Equity included

Hybrid work model

On-target earnings range

Job summary

snorkel AI is seeking a Staff-level Applied AI Engineer to deliver generative AI and machine learning solutions for enterprise customers. The role bridges cutting-edge AI research with business outcomes, partnering with clients to scope use cases, build production systems, and translate recurring challenges into reusable internal tooling and best practices.

The role involves end-to-end collaboration with customers on GenAI/ML initiatives, designing AI systems (including retrieval-augmented

Qualifications

• 3+ years of customer-facing AI/ML design and delivery.
• Strong Python and production-grade software skills.
• Experience with retrieval, RAG, and LLM orchestration.
• Excellent communication with technical and executive audiences.

Responsibilities

• Partner with enterprise customers end-to-end on GenAI and ML initiatives.
• Design and implement AI systems (retrieval-augmented generation, fine-tuning pipelines, agentic workflows).
• Build augmented datasets and evaluation harnesses for reliability and trust.
• Cultivate relationships with customer leadership and technical stakeholders.
• Collaborate with pre-sales solutions and product teams to map needs to platform capabilities.
• Standardize solutions, contribute to internal tooling, and lead enablement workshops.

Skills

Python proficiency

Customer-facing

ML systems design

Stakeholder collaboration

Presentation skills

Education

Bachelor's degree

Job description

snorkel AI is seeking a Staff-level Applied AI Engineer to deliver generative AI and machine learning solutions for enterprise customers. The role bridges cutting-edge AI research with business outcomes, partnering with clients to scope use cases, build production systems, and translate recurring challenges into reusable internal tooling and best practices.

The role involves end-to-end collaboration with customers on GenAI/ML initiatives, designing AI systems (including retrieval-augmented