Principal Machine Learning Engineer, Gopuff

Consumer Personalization & Generative AI

$175-270k

+ Discretionary annual cash bonus and participation in Gopuff’s equity incentive plan

SQL

AWS

GCP

Python

Tensorflow

Azure

PyTorch

Junior, Mid, Senior and Expert level

Boston

Miami

New York

San Francisco Bay Area

Remote from US

Groceries, alcohol, home essentials delivery service

Job no longer available

Groceries, alcohol, home essentials delivery service

1001+ employees

B2CRetailFoodConsumer GoodsDeliveryeCommerce

Job no longer available

$175-270k

+ Discretionary annual cash bonus and participation in Gopuff’s equity incentive plan

SQL

AWS

GCP

Python

Tensorflow

Azure

PyTorch

Junior, Mid, Senior and Expert level

Boston

Miami

New York

San Francisco Bay Area

Remote from US

1001+ employees

B2CRetailFoodConsumer GoodsDeliveryeCommerce

Company mission

To deliver food, drink, supplies, and essentials to customers' doorsteps, safely and quickly.

Job

Company

Role

Who you are

MS/PhD in Computer Science, Statistics, Mathematics or a related field with 2+ years of experience building generative-AI systems (or 8+ years of industry experience in data science)
Demonstrated experience fine-tuning LLMs using LoRA/qLoRA, adapting models through RAG pipelines, and optimizing with transformer architectures
Proficiency in prompt engineering, RLHF and model optimization
Hands-on expertise with Hugging Face Transformers, LangChain, LlamaIndex and vector databases (e.g., Pinecone, FAISS)
Strong skills in Python and ML frameworks (PyTorch, TensorFlow, JAX); experience with cloud platforms (AWS, GCP, Azure) and MLOps tools (MLflow, Databricks, etc.)
Experience working with large datasets and SQL; ability to write scalable, production-quality code
Excellent communication and collaboration skills to partner across technical and business teams
A passion for building AI that understands and anticipates customer needs while ensuring responsible and fair use of technology

What the job involves

Gopuff’s Data Science team powers the personalized search, browse and recommendation experiences that shape how customers discover daily goods
We are expanding our mission to include cutting-edge generative-AI capabilities
This role will lead the design and deployment of LLM-driven models that deeply understand customer needs and deliver personalized, timely experiences
You will partner with product managers, engineers and researchers to adapt pre-trained large language models (LLMs) to Gopuff’s unique business challenges, fine-tune models using LoRA/qLoRA, build retrieval-augmented generation (RAG) pipelines, and drive innovation from prototype through production
Understand customer needs through AI: Build models that interpret intent and context to provide the right product, recommendation or experience at the right moment
Fine-tune and adapt LLMs: Apply LoRA/qLoRA and RAG techniques to customize state-of-the-art LLMs for Gopuff’s domain, using frameworks such as Hugging Face, LangChain and LlamaIndex
Architect personalization systems: Design robust pipelines for search, retrieval and ranking that combine generative AI with classical ML, leveraging vector databases and prompt/context optimization
Drive algorithmic innovation: Explore and apply new methods in deep learning, reinforcement learning, multi-task learning and embeddings to improve personalization, recommendations and discovery
Develop conversational and Q&A experiences: Build interactive agents that can answer questions, guide product discovery and engage with customers in natural language
Deploy at scale: Collaborate with MLOps and engineering teams to productionize models with high scalability, reliability and low-latency response times
Evaluate and optimize: Define metrics, design A/B tests and perform offline/online evaluations to measure model performance, customer satisfaction and business impact
Collaborate and educate: Work with product, engineering, design, analytics and leadership teams to translate business needs into AI solutions and communicate data-science concepts clearly
Mentor and lead: Provide technical leadership and mentorship to data scientists and ML engineers, fostering a culture of responsible, customer-focused AI
Stay ahead of the curve: Continuously track emerging LLM architectures, tools and techniques, and integrate them into Gopuff’s AI roadmap

Our take

Gopuff was an early player in the last-mile delivery space, offering consumers access to a wide range of consumer goods (including food and alcohol) with delivery in ~30 minutes through its network of micro fulfillment centers, from which a fleet of drivers pick up and drop off orders.

Gopuff currently operates in over 1,000 cities and is adding more. The company has also made several strategic acquisitions to charge its growth – including UKs Fancy and Dija, and US BevMo!. However, the company faces increased competition on all sides, from Getir (who recently acquired Gorillas), Glovo, and Zapp, as well as high operating costs.

To combat its competition, the company has added a range of new capabilities to its platform, launching features to eliminate former pain points by including advance order scheduling, gifting, and in-store pickup.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Top investors

-11% employee growth in 12 months

Glassdoor (2.7)

Company

Funding (last 2 of 11 rounds)

Nov 2025

$250m

LATE VC

Dec 2021

$1.5bn

CONVERTIBLE

Total funding: $5.2bn

Company HQ

Northern Liberties, Philadelphia, PA

Leadership

Yakir Gola

(Co-Founder & Co-CEO)

Co-founded GoPuff whilst studying at Drexel University.

Rafael Ilishayev

(Co-Founder & Co-CEO)

Rafael studied at Drexel University with Yakir, where they co-founded Gopuff together in October 2013, and have been co-CEOs since.

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