Applied AI Engineer - Enterprise Solutions
Snorkel AIBase Salary
$175k - $300k/yr
Responsibilities
- Build and deploy customer-facing generative AI and machine learning solutions from use-case scoping and data exploration through model development and deployment.
- Develop RAG systems, fine-tuning pipelines, prompt-engineering recipes, and agentic workflows.
- Create augmented datasets and evaluation workflows to improve model reliability, transparency, and stakeholder trust.
- Manage relationships with customer leadership and stakeholders throughout AI project development and deployment.
- Collaborate with pre-sales Solutions and Product teams to map customer needs to capabilities and identify roadmap gaps.
- Standardize repeatable solutions into internal tooling, recipes, workflows, and best practices.
- Educate stakeholders and lead customer enablement workshops on AI capabilities, tradeoffs, and appropriate use cases.
- Represent customer feedback and emerging AI, data science, and workflow needs to product teams.
- Travel up to 25% annually.
Requirements
- Bachelor of Science in a quantitative field such as Computer Science, Engineering, Mathematics, or Statistics, or comparable degree/experience.
- At least 3 years of customer-facing experience designing and implementing AI/ML solutions.
- Proficiency in Python and software engineering fundamentals including modular design, testing, profiling, packaging, type validation, typed data modeling, and environment configuration.
- Experience with Python tools and libraries such as pydantic, mypy, pytest, poetry, FastAPI, msgspec, Ray, and Airflow.
- Expertise with classical ML, deep learning, foundation-model, vector and embedding, data processing, retrieval, evaluation, and LLM orchestration tooling.
- Experience with scikit-learn, PyTorch, Hugging Face Transformers, FAISS, pandas, Spark, Chroma, Weaviate, LlamaIndex, LangGraph, or CrewAI.
- Experience leading strategic customer-facing initiatives and collaborating with business stakeholders to achieve successful ML outcomes.
- Strong presentation, teaching, and enablement skills for technical and executive audiences.
- Ability to work in a fast-paced environment and balance priorities across multiple projects.
Benefits
- Hybrid work in San Francisco, California or New York, New York.
- Annual travel of up to 25%.
- Employee stock options are included in offers.
- Opportunities for career growth, technical development, leadership exploration, and cross-functional learning.
- Equal employment opportunity and reasonable accommodation are provided.
Tech Stack
Categories
About Snorkel AI
Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine platform technology with research-driven data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Snorkel led the development of Senior SWE-Bench and launched Open Benchmarks Grants with a $3 million commitment to support open-source datasets, benchmarks, and evaluation research. Supported projects include Agents’ Last Exam, OSWorld 2.0, Terminal-Bench, Continual Learning Bench, and SlopCode Bench. Learn more at snorkel.ai or follow @SnorkelAI.