Machine Learning Solutions Engineer

May 3

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Gretel.ai

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The Developer Stack for Synthetic Data.

Generative AI • Synthetic Data • Machine Learning • Privacy • AI

11 - 50

Description

• As a Machine Learning Solutions Engineer, you'll articulate Gretel’s mission and value to new prospects and existing customers, working side-by-side with our sales, engineering, product, and applied science teams. You will play a critical role in driving the success of our GTM efforts by helping to differentiate the platform throughout the sales process, drive value-centered proof of concepts (POC) and paid pilots, and help existing customers better utilize synthetic data via repeatable, scalable use cases. You will echo and amplify our data science thought leadership by guiding meaningful and valuable customer experimentation with the platform. • Build custom prototypes and product demos that highlight end-to-end operationalized use cases of Gretel. These may be both for pre and post sales objectives. • Be the voice of the customer, communicating back experimental results and empirical experience gained from the field and critical for our internal applied science research. • Be the voice of the customer by also proactively identifying opportunities in our product based on trends identified across customer needs, and build solutions to address these emerging patterns. • Conduct and guide research in the field, working with our most pioneering customers to advance what is possible with our platform. • Augment the technical discovery during the sales lifecycle to deeply understand prospects’ ML and engineering requirements • Help the account teams differentiate proposed approaches versus open source and competitive solutions. • Stay up-to-date with industry trends, best practices, and advancements in generative AI, data privacy, and cloud infrastructure.

Requirements

• 5+ years of experience in a technical customer-facing role serving Enterprise customers and showcasing a track record of successful technical sales support. Ideally this will include value based selling of a hybrid solution. • Fluency in Python, utilizing Collab or Jupyter notebooks, and working with open-source libraries. • Deep experience working with data pipelines and orchestration / tooling for the modern data stack. • Previous hands on engineering experience in Data Engineering and MLOps. • Exceptional presentation and communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences. • Ability to operate with high horsepower, adept at frequent context switching and working on multiple projects at once with expansive ownership and prioritization. • Capable of owning problems end-to-end, a deep curiosity to acquire knowledge, and the humility to figure out what is missing to get the job done. • Passion for thriving in a dynamic and ambiguous environment. • Willingness to travel occasionally (up to 20%) for customer meetings, conferences, and industry events as needed. • Fluency in English is required; proficiency in additional languages spoken in the EMEA region is a plus.

Benefits

• 11 paid holidays • Generous Accrued Time Off increasing with years of service • Generous paid sick time • Annual day of service