Principal Applied Scientist

Summary

Join Highspot as a Principal Search & Recommendation Engineer to lead the design and evolution of intelligent systems for content discovery and personalization. You will leverage expertise in machine learning, information retrieval, and large-scale systems to enhance AI capabilities and mentor engineers. This role involves end-to-end development of search and recommendation systems, driving technical strategy, collaborating with cross-functional teams, and influencing platform-level decisions. You will need 8+ years of experience in building and scaling search or recommendation systems, deep expertise in information retrieval and ranking algorithms, and strong programming skills. Highspot offers a competitive salary, equity, benefits, flexible work environment, and a collaborative team culture.

Requirements

• 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)

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• 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
• Comprehensive medical, dental, vision, disability, and life benefits
• Health Savings Account (HSA) with employer contribution
• 401(k) Matching with immediate vesting on employer match
• Flexible PTO
• 8 paid holidays and 5 paid days for Annual Holiday Week
• Quarterly Recharge Fridays (paid days off for mental health recharge)
• 18 weeks paid parental leave
• Access to Coaches and Therapists through Modern Health
• 2 volunteer days per year
• Commuting benefits