Principal Data Scientist, Gopuff
Consumer Personalization & Generative AI
$175-270k
+ Discretionary annual cash bonus and participation in Gopuff’s equity incentive plan
Food, alcohol, and daily essentials delivery service
Be an early applicant
Food, alcohol, and daily essentials delivery service
1001+ employees
Be an early applicant
$175-270k
+ Discretionary annual cash bonus and participation in Gopuff’s equity incentive plan
1001+ employees
Company mission
To deliver food, drink, supplies, and essentials to customers' doorsteps, safely and quickly.
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 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.
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. After abandoning plans to IPO in mid-2022, it is focusing back on profitability, though the company has faced some scrutiny over its methods and has had to search further afield for funding at a time when venture capital is scarce. Regardless, Gopuff is well set to remain a major player in the market.
Freddie
Company Specialist at Welcome to the Jungle
Insights
-11% employee growth in 12 months
Company
Funding (last 2 of 10 rounds)
Dec 2021
$1.5bn
CONVERTIBLE
Jul 2021
$1bn
SERIES H
Total funding: $5.0bn
Company benefits
- Gopuff employee discount
- Career growth opportunities
- Internal rewards programs
- Annual performance appraisal and bonus
- Equity program
Company HQ
Northern Liberties, Philadelphia, PA
Leadership
Yakir Gola
(Co-CEO & Co-Founder)Founded GoPuff whilst studying at Drexel University.
Rafael Ilishayev
(Co-CEO & Co-Founder)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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