Staff Applied AI Engineer – Enterprise AI Solutions

Snorkel AI

. Partner with customers to build and deploy Gen AI and machine learning solutions from use case scoping and data exploration through model development and deployment .

Posted 10/6/2026full-timeUnited StatesLead💰 $230,000 - $360,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI and machine learning solutions, with a strong focus on customer engagement and education. Proficient in Python and modern AI tools, capable of developing reliable models and facilitating stakeholder collaboration.

Highest-signal resume keywords

Python ProficiencyAI/ML Solution DesignCustomer-Facing ExperienceApplied AI ExpertisePresentation Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningModel DevelopmentData ExplorationPrompt EngineeringEvaluation WorkflowsModular DesignTestingProfilingPackagingSynthetic Dataset Curation

Soft Skills

Customer Relationship ManagementTeaching FocusCollaborationPresentation SkillsStakeholder Engagement

Tools & Technologies

PydanticMypyPytestFastAPIRayAirflowScikit-LearnPyTorchHugging Face TransformersFAISS

Industry Keywords

Gen AIMachine LearningAI ToolsData Science WorkflowsCustomer EnablementQuantitative FieldEvaluation WorkflowsLLM OrchestrationChromaWeaviate

Tech Stack

Tools & technologies

AirflowPandasPythonPyTorchRayScikit-LearnSpark

About the role

Key responsibilities & impact

Partner with customers to build and deploy Gen AI and machine learning solutions from use case scoping and data exploration through model development and deployment
Design custom approaches using state-of-the-art AI tools and inform the evolution of Snorkel AI’s tooling
Develop AI systems including retrieval-augmented generation, fine-tuning pipelines, prompt engineering recipes, and agentic workflows
Create augmented real-world datasets and comprehensive evaluation workflows for model reliability, transparency, and stakeholder trust
Build and manage relationships with customer leadership and stakeholders
Collaborate with pre-sales Solutions and Product teams to map customer needs, prioritize roadmap gaps, and guide project setup
Standardize solutions and contribute to internal tooling and best practices with other Applied AI Engineers
Educate stakeholders on quantitative capabilities, approach strengths and weaknesses, and suitable problems for Snorkel AI
Represent customer needs for new AI paradigms and data science workflows and share feedback with product teams
Conduct customer enablement workshops
Research and utilize state-of-the-art Gen AI and ML techniques to deliver customer solutions

Requirements

What you’ll need

B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience
3+ years of customer-facing experience in the design and implementation of AI/ML solutions
Proficiency in Python and strong software engineering fundamentals, including modular design, testing, profiling, and packaging
Experience with modern Python constructs and libraries including pydantic, mypy, pytest, poetry, FastAPI, msgspec, Ray, and Airflow
Expertise across the Applied AI stack, including scikit-learn, PyTorch, Hugging Face Transformers, FAISS, pandas, Spark, Chroma, Weaviate, synthetic dataset curation, evaluation workflows, LLM orchestration, LlamaIndex, LangGraph, and CrewAI
Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to achieve successful ML outcomes
Strong teaching and enablement focus
Outstanding presentation skills for technical and executive audiences
Ability to work in a fast-paced environment and balance priorities across multiple projects
Annual travel availability of up to 25%

Benefits

Comp & perks

Equity included in all offers
Meaningful opportunities to shape priorities and initiatives and influence key strategic decisions
Opportunities to deepen technical expertise, explore leadership opportunities, and learn new skills across multiple functions
Career support in an environment designed for growth, learning, and shared success
Reasonable accommodation for individuals with disabilities during application, interview, and employment processes