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Staff Applied AI Engineer, Enterprise AI Solutions
Lead customer-facing generative AI and machine learning engagements at Snorkel AI, from scoping and data exploration through deployment. Build RAG systems, agentic workflows, evaluation frameworks, and reusable tools for enterprise applications.
Сипаттама
- Partner with customers to scope, develop, and deploy generative AI and machine learning solutions.
- Create tailored approaches with advanced AI tools while helping shape Snorkel AI’s platform and tooling.
- Build applied AI systems such as retrieval-augmented generation applications, fine-tuning pipelines, prompt engineering methods, and agentic workflows.
- Produce augmented real-world datasets and robust evaluation processes that improve reliability, transparency, and stakeholder confidence.
- Develop and maintain relationships with customer executives and other key stakeholders.
- Work with pre-sales Solutions and Product teams to understand customer needs, identify roadmap priorities, and plan engagements.
- Standardize successful solutions and strengthen internal tools and practices with fellow Applied AI Engineers.
- Explain quantitative capabilities, methodological tradeoffs, and appropriate use cases for Snorkel AI to stakeholders.
- Bring customer feedback on emerging AI methods and data science workflows to product teams.
- Lead workshops that enable customers to use and understand delivered solutions.
- Investigate and apply leading generative AI and machine learning methods to solve customer problems.
Талаптар
- Bachelor’s degree in a quantitative discipline such as computer science, engineering, mathematics, or statistics, or equivalent education and experience.
- At least three years of customer-facing experience designing and implementing AI or machine learning solutions.
- Proficiency in Python and strong software engineering practices, including modular architecture, testing, profiling, and packaging.
- Experience with modern Python tools and libraries such as pydantic, mypy, pytest, poetry, FastAPI, msgspec, Ray, and Airflow.
- Advanced knowledge 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.
- Demonstrated ability to lead strategic customer engagements and work with business stakeholders to deliver successful machine learning outcomes.
- Strong interest in teaching, enablement, and knowledge sharing.
- Excellent presentation skills with both technical and executive audiences.
- Ability to operate in a fast-moving environment while managing priorities across multiple projects.
- Availability to travel up to 25% annually.
Артықшылықтар
- Equity is included in every offer.
- Opportunities to shape priorities, lead initiatives, and influence important strategic decisions.
- Multiple paths to expand technical depth, pursue leadership, and build skills across functions.
- Career support within a workplace focused on growth, learning, and collective success.
- Reasonable accommodations are available for applicants and employees with disabilities throughout the application, interview, and employment process.
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