Sr. ML Engineer — Search & Personalization

Bask Health; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

Bask Health is seeking a Senior Machine Learning Engineer, Search & Personalization to design, build, and improve intelligent search, discovery, and personalization across Bask Health's platform. This hands-on role focuses on production ML systems and engineering workflows.

You will work with embeddings, ranking, retrieval pipelines, and collaborate with product, backend, frontend and applied AI teams to deliver measurable value while upholding privacy and healthcare data considerations.

Qualifications

• 5+ years of professional experience in machine learning engineering, software engineering, search engineering, or a closely related technical discipline.
• Demonstrated experience building and deploying machine learning systems in production.
• Strong programming skills in Python and experience developing production software services.
• Experience building search, recommendation, ranking, or information retrieval systems.
• Strong understanding of machine learning fundamentals and applied statistical methods.
• Familiarity with modern information retrieval techniques and search relevance optimization.
• Experience with embeddings, vector representations, or semantic similarity methods.
• Understanding of lexical search, semantic search, and hybrid retrieval approaches.
• Experience designing or integrating scalable search infrastructure.
• Strong understanding of ranking algorithms and relevance evaluation.
• Experience working with structured and unstructured datasets.
• Familiarity with data processing, feature engineering, and machine learning pipelines.
• Experience building backend APIs and integrating machine learning services into applications.
• Understanding of database design, indexing, and query performance.
• Experience evaluating model or search system performance using quantitative metrics.
• Familiarity with offline evaluation, experimentation, and performance benchmarking.
• Experience optimizing production systems for latency, scalability, and reliability.
• Understanding of cloud infrastructure and deployment practices.
• Familiarity with monitoring, logging, and troubleshooting production services.
• Strong software engineering practices, including testing, code review, and version control.
• Understanding of data privacy, access controls, and secure application design.
• Ability to translate product requirements into practical machine learning solutions.
• Experience collaborating with product managers and cross-functional engineering teams.
• Ability to independently own complex engineering projects from design through deployment.
• Strong analytical thinking, communication skills, and technical problem-solving abilities.

Responsibilities

• Design, build, and deploy machine learning systems for search, discovery, ranking, and personalization.
• Develop semantic search capabilities that improve how users find information across Bask Health's applications.
• Build and optimize retrieval pipelines using embeddings, vector search, and traditional search methods.
• Design hybrid search systems combining lexical matching, semantic retrieval, and relevance ranking.
• Develop ranking models and algorithms that prioritize useful search results.
• Build recommendation systems that surface relevant platform features, resources, or workflow information.
• Develop contextual personalization capabilities based on approved user and application signals.
• Work with product teams to identify opportunities to improve search relevance and information discovery.
• Build scalable indexing, retrieval, and search-serving infrastructure.
• Design data pipelines that support search models, ranking systems, and recommendation features.
• Develop approaches for generating, storing, updating, and evaluating embeddings.
• Experiment with learning-to-rank methods and machine learning-based relevance improvements.
• Implement query understanding, query expansion, and search intent interpretation where appropriate.
• Improve search performance across structured and unstructured data sources.
• Collaborate with applied AI engineers to support retrieval-augmented generation applications.
• Develop retrieval services that can be reused across patient, merchant, and operational applications.
• Define and track search quality metrics, including relevance, recall, precision, and ranking performance.
• Design offline evaluation datasets and benchmarking procedures for search and recommendation systems.
• Collaborate with product teams to conduct controlled experiments and measure user experience improvements.
• Optimize search latency, throughput, infrastructure utilization, and operational costs.
• Implement monitoring and observability for production search and personalization services.
• Investigate search quality issues, indexing failures, and ranking inconsistencies.
• Ensure retrieval and personalization systems respect user permissions and data access boundaries.
• Design appropriate safeguards for sensitive healthcare-related recommendations.
• Work with backend and frontend engineers to integrate search and recommendation features into production applications.
• Contribute to architecture decisions involving search infrastructure, databases, and machine learning services.
• Mentor engineers and share expertise in information retrieval, ranking, and production ML engineering.
• Own search and personalization initiatives from technical design through deployment, measurement, and ongoing improvement.

Skills

Python

ML engineering

Search engineering

Information retrieval

Ranking algorithms

Recommender systems

Embeddings

Backend APIs

Cloud infrastructure

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Tools

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Job description

Bask Health is seeking a Senior Machine Learning Engineer, Search & Personalization to design, build, and improve intelligent search, discovery, and personalization across Bask Health's platform. This hands-on role focuses on production ML systems and engineering workflows.

You will work with embeddings, ranking, retrieval pipelines, and collaborate with product, backend, frontend and applied AI teams to deliver measurable value while upholding privacy and healthcare data considerations.