Solution Engineer (Pre-Sales)
Union.aiSalary not specified
- Full Time
- Junior (1 to 2 years)
$150,000 – $180,000Compensation
Junior (1 to 2 years)Experience Level
Full TimeJob Type
UnknownVisa
AI & Machine LearningIndustries
Requirements
Candidates should have at least 2 years of experience in technical pre-sales, solutions engineering, or customer-facing technical roles, preferably in an ML/AI company. Intermediate experience with Python and a basic understanding of AI/ML concepts, especially around model deployment and inference, are required. Familiarity with open-source ML models and common LLM tools and frameworks, such as LangChain and Hugging Face, is essential. Strong communication skills are necessary to explain technical concepts clearly to diverse audiences, along with a Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Responsibilities
The Solutions Engineer will partner with the sales team to engage prospects and provide technical expertise throughout the early sales cycle. They will help conduct evaluations of Baseten's platform for prospective customers and create customized demonstrations and proof-of-concepts that highlight Baseten's capabilities in solving customer-specific AI deployment challenges. Gathering customer requirements and technical feedback to inform product roadmap decisions is key, as well as identifying common customer pain points and collaborating with product teams to address them. Staying current with industry trends, open-source ML models, and AI deployment best practices is also essential, along with partnering with the Forward Deployed Engineer team to deliver value for strategic customers.
Skills
Python
AI/ML
Model Deployment
Inference
LangChain
Hugging Face
Communication
Pre-sales
Solutions Engineering
Baseten
Platform for deploying and managing ML models
About Baseten
Baseten provides a platform for deploying and managing machine learning (ML) models, aimed at simplifying the process for businesses. Users can select from a library of open-source foundation models and deploy them with just two clicks, making it easier to implement ML solutions. The platform features autoscaling, which adjusts resources based on demand, and comprehensive monitoring tools for tracking performance and troubleshooting. A key differentiator is Baseten's open-source model packaging framework, Truss, which allows users to package and deploy custom models easily. The company operates on a usage-based pricing model, where clients pay only for the time their models are actively deployed, helping them manage costs effectively.
San Francisco, CaliforniaHeadquarters
2019Year Founded
$58.4MTotal Funding
SERIES_BCompany Stage
AI & Machine LearningIndustries
51-200Employees