Principal Full-Stack Data Scientist – Foundational Models

Stitch Fix

. Design, develop, evaluate, and productionize machine learning models improving personalization and recommendation systems .

Posted 11/3/2026full-timeRemote • United StatesLead💰 $200,000 - $237,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying machine learning solutions, particularly in personalization and recommendation systems, while effectively communicating complex concepts to diverse stakeholders. Proficient in managing the full ML lifecycle, from problem formulation to production deployment and evaluation.

Highest-signal resume keywords

Machine Learning Solutions DesignPython ProgrammingDeep Learning Frameworks (PyTorch, TensorFlow)SQL and Distributed Data Processing (Spark)Model Evaluation and Experimentation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningPersonalization SystemsRecommendation SystemsRepresentation LearningModel DeploymentData ExplorationA/B TestingModel Performance MeasurementProduction-Grade CodeMultimodal Modeling

Soft Skills

Strong Communication SkillsCollaborationMentoringIntellectual CuriosityInfluencing Technical Decisions

Tools & Technologies

PythonSQLSparkPyTorchTensorFlowDistributed Data Processing ToolsBehavioral DatasetsProduct Datasets

Industry Keywords

Machine Learning LifecycleModel QualityScalabilityReliabilityComputational Cost

Tech Stack

Tools & technologies

PythonPyTorchSparkSQLTensorflow

About the role

Key responsibilities & impact

Design, develop, evaluate, and productionize machine learning models improving personalization and recommendation systems
Advance foundational modeling capabilities, including client and item representations, embeddings, retrieval, ranking, recommendation models, and assortment generation
Explore and apply LLMs, deep learning, representation learning, multimodal modeling, and generative approaches
Own the full ML lifecycle from problem formulation and data exploration through modeling, experimentation, deployment, monitoring, and iteration
Design offline evaluations and online experiments to measure model performance and client and business impact
Work with large-scale behavioral and product datasets using Python, SQL, and distributed data-processing tools
Build production-quality ML solutions emphasizing scalability, reliability, latency, observability, and cost
Collaborate with Product, Engineering, and Data Science teams to translate downstream needs into reusable foundational ML capabilities
Contribute to technical direction through design discussions, code reviews, research, prototyping, and best practices
Communicate technical concepts, modeling approaches, tradeoffs, and recommendations to technical and non-technical stakeholders
Mentor and collaborate with Data Scientists and engineers

Requirements

What you’ll need

Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required
8+ years of experience in design and deployment of machine learning solutions, ideally in personalization, recommendation systems, representation learning, or search
Strong ability to architect technical solutions and write production-grade code in Python
Ability to independently drive ambiguous machine learning problems from initial exploration and prototyping through production deployment, monitoring, iteration, and measurable impact
Experience working with large-scale datasets using SQL and distributed data-processing technologies such as Spark
Experience with modern deep-learning frameworks such as PyTorch or TensorFlow
Strong understanding of model evaluation and experimentation, including offline evaluation, A/B testing, and translating model improvements into measurable product or business outcomes
Ability to reason about production ML system tradeoffs, including model quality, latency, scalability, reliability, and computational cost
Strong communication and collaboration skills, with the ability to influence technical decisions and communicate complex concepts to technical and non-technical stakeholders
Intellectual curiosity and demonstrated ability to learn and apply new machine learning techniques to practical problems

Benefits

Comp & perks

Competitive salary
Equity
Annual bonus
New hire and ongoing restricted stock unit grants, depending on employee and company performance
Medical benefits
Dental benefits
Vision benefits
Other inclusive health and wellness benefits
Comprehensive compensation package