B.S. in Computer Science, Engineering, Math/Statistics, or equivalent experience
8+ years in customer-facing technical roles (pre-sales, solutions engineering, or applied AI), including discovery, scoping, demos, proof-of-value engagements, and RFP responses
Hands-on Python experience and familiarity with the modern Gen AI stack - LLM ecosystems, RAG, vector databases, data processing, synthetic dataset curation, evaluation workflows, LLM orchestration and agent authoring tools
Expertise across the predictive ML stack, including classical ML (e.g., scikit-learn) and data processing frameworks (e.g., pandas, Spark)
Ability to operate in fast-paced environments and rapidly build prototypes (ML solutions, RAG systems, prompt-based workflows, fine-tuned models, agentic systems) that demonstrate business value
Able to translate ambiguous business problems into testable technical approaches and measurable success criteria
Strong presentation and storytelling skills with the ability to engage both technical and executive audiences with credibility
Experience estimating scope and producing technical content for proposals and Statements of Work
Locations
New York; San Francisco Bay Area; Austin; Dallas; Seattle; Atlanta; Nashville; Boston; Remote - US
Actual compensation will be determined based on factors including skills, qualifications, experience, and geographic location
Salary range(s) for this role
Be Your Best at Snorkel
Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success