Senior Machine Learning Engineer, Recommender Systems

undefined ago • 7 Years + • System Design • $150,000 PA - $250,000 PA

Job Summary

Job Description

As a Machine Learning Engineer – Recommender Systems, you’ll play a central role in improving HP’s Retrieval-Augmented Generation (RAG) pipelines for private and local data. You’ll build intelligent, context-aware retrieval systems that enhance user interactions with documents, meetings, and applications—all on-device. This role blends deep ML experience with product-focused engineering.
Must have:
  • Design, implement, and scale recommendation and retrieval algorithms.
  • Improve vector search and similarity matching models.
  • Analyze user interactions and system performance.
  • Deploy fast and efficient RAG workflows.
  • Build and maintain retrieval indexes.
  • 7+ years software development experience with ML engineering.
  • Strong foundation in recommender systems, embeddings, ranking models.
  • Experience building or scaling document search/retrieval systems.
  • Familiarity with vector databases (FAISS, Pinecone, Qdrant).
  • Proficient in Python and one systems language (C++, Java).
Good to have:
  • Background in LLM integration or fine-tuning for RAG workflows.
  • Industry experience at companies like Google, Meta, or Twitter.
  • Experience with ML pipeline tools (Airflow, Ray, TorchServe).
  • Previous experience improving search relevance, click-through rate, or long-term engagement.
Perks:
  • Health insurance
  • Dental insurance
  • Vision insurance
  • Long term/short term disability insurance
  • Employee assistance program
  • Flexible spending account
  • Life insurance
  • Generous time off policies (4-12 weeks fully paid parental leave, 11 paid holidays, flexible paid vacation and sick leave)

Job Details

Who We Are

HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates.

We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless.

We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset.

By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work.

Join us as we reinvent work, so people everywhere can do their best work.

About The Role

As a Machine Learning Engineer – Recommender Systems, you’ll play a central role in improving HP’s Retrieval-Augmented Generation (RAG) pipelines for private and local data. You’ll build intelligent, context-aware retrieval systems that enhance user interactions with documents, meetings, and applications—all on-device. This role blends deep ML experience with product-focused engineering.

What You Might Do

  • Design, implement, and scale recommendation and retrieval algorithms for our AI Companion app
  • Improve vector search and similarity matching models to identify relevant documents across structured and unstructured data
  • Analyze user interactions and system performance to guide algorithmic improvements
  • Work across ML, infrastructure, and product teams to deploy fast and efficient RAG workflows
  • Build and maintain retrieval indexes optimized for latency and memory

Essential Qualifications

  • 7+ years of software development experience with exposure to ML engineering
  • Strong foundation in recommender systems, embeddings, and ranking models
  • Experience building or scaling document search or retrieval systems
  • Familiarity with vector databases (e.g., FAISS, Pinecone, Qdrant)
  • Proficient in Python and one systems language (e.g., C++, Java)

Preferred Skills

  • Background in LLM integration or fine-tuning for RAG workflows
  • Industry experience at companies like Google (Search, YouTube), Meta (Feed, Ads), or Twitter (Timeline, Trends)
  • Experience with ML pipeline tools (Airflow, Ray, TorchServe)
  • Previous experience improving search relevance, click-through rate, or long-term engagement

Compensation & Benefits (Full-Time Employees)

The salary range for this role is listed above. Final salary offered is based upon multiple factors including individual job-related qualifications, education, experience, knowledge and skills.

At HP IQ, we offer a competitive and comprehensive benefits package, including:

  • Health insurance
  • Dental insurance
  • Vision insurance
  • Long term/short term disability insurance
  • Employee assistance program
  • Flexible spending account
  • Life insurance
  • Generous time off policies, including;
  • 4-12 weeks fully paid parental leave based on tenure
  • 11 paid holidays
  • Additional flexible paid vacation and sick leave

Why HP IQ?

HP IQ is HP’s new AI innovation lab, building the intelligence to empower humanity—reimagining how we work, create, and connect to shape the future of work.

  • Innovative Work

Help shape the future of intelligent computing and workplace transformation.

  • Autonomy and Agility

Work with the speed and focus of a startup, backed by HP’s scale.

  • Meaningful Impact

Build AI-powered solutions that help people and organisations thrive.

  • Flexible Work Environment

Freedom and flexibility to do your best work.

  • Forward-Thinking Culture

We learn fast, stay future-focused, and imagine what comes next—together.

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About The Company

Our vision is to create a world where innovation drives extraordinary contributions to humanity. This vision guides everything we do, how we do it, and why we do it.

Our technology – a product and service portfolio of personal systems, printers, and 3D printing solutions – was created to inspire our vision and we are doing everything in our power across climate action, human rights, and digital equity to make it so.

We believe thoughtful ideas can come from anyone, anywhere, at any time. And all it takes is one to change the world.

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