Solutions Engineer
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Role details
Tech stack
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Job description
You will lead customers to success by teaching our product to new users, consulting on best practices, and bridging the gap between technical and business worlds. You must be equally comfortable having deep technical discussions with data scientists/engineers and demonstrating the business value., * Advise & Consult: Partner with some of the most sophisticated ML / GenAI teams in the world, advising them on GenAI and ML best practices.
- Demonstrate Value: Deliver engaging ML and LLM product demos to both technical and business stakeholders.
- Drive Success: Run strategic business reviews for customers in partnership with our Sales team, and spearhead expansion opportunities within existing accounts.
- Collaborate Cross-Functionally: Interface with Pre-Sales Engineering to gather client goals/KPIs and partner with Product and Engineering to help drive our product roadmap.
Requirements
Do you have experience in Machine learning libraries?, * Technical Background: Previous experience as a Data Scientist, Machine Learning Engineer, or as an Engineer working with ML models or GenAI applications in production.
- Cloud & Code: Comfort working in public Cloud environments (AWS, Azure, GCP) and proficiency in at least one programming language (Python, JS/TS, Java, Go, etc.).
- ML/DS Knowledge: Solid understanding of ML/DS concepts, model evaluation strategies, and lifecycles (feature generation, training, deployment, batch/real-time scoring via REST APIs).
- Frameworks: Knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and LLM/Agentic frameworks (LlamaIndex, LangGraph, DSPy).
- Core Skills: Strong communication skills with the ability to simplify complex technical concepts, paired with a self-learner mindset that thrives on technical complexity.
Bonus Points (Not Required)
- Prior customer-facing experience (Solutions Architect, Implementation Specialist, Sales Engineer, Customer Success Engineer, Consultant, or Professional Services).
- Experience with applications deployed via Kubernetes.
- Prior experience demoing technical products to dual audiences (business and technical).
Benefits & conditions
4.04.0 out of 5 stars San Francisco, CA Remote $125,000 - $175,000 a year - Full-time
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