Principal Search & Recommendation Engineer
Highspot
Job Summary
Highspot is seeking a Principal Search & Recommendation Engineer to lead the design and evolution of intelligent systems for discovery and personalization on their platform. This role involves working at the intersection of machine learning, information retrieval, and large-scale systems. Responsibilities include leading end-to-end development of search and recommendation systems, driving technical strategy in areas like relevance and personalized ranking, and collaborating with product and data teams. The role also involves mentoring engineers and fostering technical excellence. The ideal candidate will have 8+ years of experience in building scalable search or recommendation systems, deep expertise in information retrieval and ranking algorithms, strong programming skills, and familiarity with LLMs and vector search.
Must Have
- 8+ years of experience in search/recommendation systems
- Expertise in information retrieval and ranking algorithms
- Strong Python, Java, or Scala skills
- Experience with ML/IR frameworks
- Familiarity with LLMs and vector search
- Proven leadership and mentoring skills
Good to Have
- Experience with personalization
- Published work in IR/ML conferences
- Contributions to open-source projects
- Experience with experimentation practices
Perks & Benefits
- Competitive salary, equity, and benefits
- Flexible work environment with remote options
- Collaborative and inclusive team culture
- Solve high-impact technical problems
- Comprehensive medical, dental, vision, disability, and life benefits
- Health Savings Account with employer contribution
- 401(k) Matching with immediate vesting
- Flexible PTO
- 8 paid holidays and 5 paid days for Annual Holiday Week
- Quarterly Recharge Fridays
- 18 weeks paid parental leave
- Access to Coaches and Therapists
- 2 volunteer days per year
- Commuting benefits
Job Description
What You'll Do
- Lead the end-to-end development of modern search and recommendation systems, from architecture to production deployment.
- Drive technical strategy and innovation in search relevance, personalized ranking, semantic search, and ML-powered retrieval/grounding.
- Collaborate with product, design, and data teams to define and deliver intelligent user experiences.
- Influence platform-level decisions on data pipelines, experimentation frameworks, and performance optimization.
- Mentor engineers, foster technical excellence, and promote a culture of learning and innovation.
Your Background
- 8+ years of experience building and scaling search or recommendation systems in production environments.
- Deep expertise in information retrieval, ranking algorithms, collaborative filtering, and/or neural search techniques.
- Strong programming skills in Python, Java, or Scala; experience with ML and IR frameworks such as Elasticsearch, FAISS, TensorFlow, or PyTorch.
- Familiarity with LLMs, embeddings, and modern vector search infrastructure.
- Proven leadership in cross-functional environments with a track record of mentoring and guiding technical teams.
- Strong grasp of MLOps practices and experience with cloud-native ML infrastructure (e.g., AWS, GCP).
Nice To Have
- Experience with personalization, multi-objective optimization, or exploration/exploitation strategies.
- Published work in top-tier IR or ML conferences, or contributions to relevant open-source projects.
- Experience driving different experimentation practices for fast iterating search/recommendation quality cases.
Why You'll Love HIghspot
- Competitive salary, equity, and benefits.
- Flexible work environment with remote options.
- Collaborative and inclusive team culture.
- A chance to solve high-impact technical problems with a team that values craftsmanship, innovation, and growth.