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Principal Machine Learning Engineer - Consumer Personalization & Generative AI
Principal Machine Learning Engineer - Consumer Personalization & Generative AIGopuff • Boston, Massachusetts, United States, 02108
Principal Machine Learning Engineer - Consumer Personalization & Generative AI

Principal Machine Learning Engineer - Consumer Personalization & Generative AI

Gopuff • Boston, Massachusetts, United States, 02108
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  • [job_card.full_time]
[job_card.job_description]

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.

You Will :

  • 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.

You Have :

  • 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.
  • Compensation :

  • Gopuff pays employees based on market pricing and pay may vary depending on your location. The salary range below reflects what we’d reasonably expect to pay candidates. A candidate’s starting pay will be determined based on job-related skills, experience, qualifications, interview performance, and market conditions. These ranges may be modified in the future. Exceptions may be made for exceptional individuals. For additional information on this role’s compensation package, please reach out to the designated recruiter for this role.
  • This role is eligible for a discretionary annual cash bonus and participation in Gopuff’s equity incentive plan.
  • Base Salary Range : $175,000 - $270,000
  • What We Offer :

  • Medical / Dental / Vision Insurance
  • 401(k) Retirement Savings Plan
  • HSA or FSA eligibility
  • Long and Short-Term Disability Insurance
  • Mental Health Benefits
  • Fitness Reimbursement Program
  • 25% employee discount & FAM Membership
  • Flexible PTO
  • Group Life Insurance
  • EAP through AllOne Health (formerly Carebridge)
  • At Gopuff, we know that life can be unpredictable. Sometimes you forget the milk at the store, run out of pet food for Fido, or just really need ice cream at 11 pm. We get it—stuff happens. But that’s where we come in, delivering all your wants and needs in just minutes.

    And now, we’re assembling a team of motivated people to help us drive forward that vision to bring a new age of convenience and predictability to an unpredictable world.

    Like what you’re hearing? Then join us on Team Blue.

    #LI-GOPUFF

    Gopuff is an equal employment opportunity employer, committed to an inclusive workplace where we do not discriminate on the basis of race, sex, gender, national origin, religion, sexual orientation, gender identity, marital or familial status, age, ancestry, disability, genetic information, or any other characteristic protected by applicable laws. We believe in diversity and encourage any qualified individual to apply.

    PI40e27b9d056e-30511-38813629

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    Principal Machine Learning Engineer • Boston, Massachusetts, United States, 02108

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