Founding ML/Data Science Engineer

Founding ML/Data Science Engineer

Location: San Francisco, CA (Hybrid) Employment Type: Full-time

About the Role

Our client is building the revenue execution system for B2B enterprises, tackling the underpenetrated space of post-sales enablement. They are combining LLMs with structured customer data to automate account scoring, cohort segmentation, and expansion playbooks. As a Founding ML/Data Science Engineer, you'll work directly with the founders to architect, build, and scale this platform from 0 to 1, with full ownership of core features.

This role requires a hybrid engineer who can both architect production ML systems and make sophisticated modeling decisions. You'll need to be equally comfortable with classical ML and cutting-edge language models.

Core Responsibilities

• Design end-to-end ML systems, covering model selection, experimentation, and production deployment.
• Build feature engineering pipelines to extract signal from both structured business data and unstructured text.
• Develop hybrid ML/LLM systems, knowing how and when to leverage traditional ML versus language models for a given problem.
• Own the full modeling lifecycle: EDA, feature engineering, training, validation, and drift monitoring.

• 3+ years of experience in applied ML.
• Strong ML fundamentals (gradient descent, regularization, bias-variance tradeoffs).
• Experience with the full spectrum of machine learning: classical ML, deep learning, and LLMs.
• Production experience with model serving, feature stores, and training pipelines.
• Statistical rigor in experimental design, hypothesis testing, and causal inference.
• Proven ability to ship end-to-end ML products.

• 3+ years of experience in applied ML.
• Strong ML fundamentals (gradient descent, regularization, bias-variance tradeoffs).
• Experience with the full spectrum of machine learning: classical ML, deep learning, and LLMs.
• Production experience with model serving, feature stores, and training pipelines.
• Statistical rigor in experimental design, hypothesis testing, and causal inference.
• Proven ability to ship end-to-end ML products.

Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.

About MLabs
MLabs is a full-stack software consultancy working with leading blockchain, AI, and tech startups worldwide. We’re supporting this client with their hiring, and you’ll be joining their team directly.

👉 Apply now to be part of one of the most exciting AI startups in San Francisco.

Commitment to Equality and Accessibility:

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing [email protected].

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