Job Description
Job Description
Designs, develops, and implements methods, processes, and systems to consolidate and
analyze diverse data sets including structured and unstructured.
Develop software programs, algorithms, dashboards, information tools, and queries to
clean, model, integrate and evaluate datasets. Keeps abreast of new analytic
methodologies and technologies.
Collaborate with functional business units to drive business solutions and direction.
Key Responsibilities include but not limited to:
Design, implement, and maintain enterprise-scale search solutions using Apache Solr
Develop and optimize semantic search capabilities using vector embeddings and neural
search models
Build custom indexers and indexing pipelines that support vector embeddings alongside
traditional text fields
Implement and tune Approximate Nearest Neighbor (ANN) algorithms for efficient
similarity search at scale
Design and optimize similarity functions (cosine, dot product, Euclidean) for various
search use cases
Build hybrid search systems that combine traditional keyword-based search with vector-
based semantic search
Perform traditional relevancy engineering including query analysis, field weighting,
boosting strategies, and result tuning
Conduct relevancy analysis using quantitative metrics and qualitative evaluation methods
Monitor search performance metrics and implement continuous improvements
Work cross-functionally with product, engineering, and data teams to define search
requirements
Required Qualifications:
5+ years of hands-on experience with Apache Solr or Lucene in production environments
Strong expertise in traditional relevancy engineering including query parsing, field
boosting, function queries, and relevance tuning
Proven experience conducting relevancy analysis using both automated metrics and
manual evaluation techniques
Strong expertise in vector embeddings and their application to semantic search
Proven experience building hybrid search systems that combine keyword and vector-
based approaches
Knowledge of search relevance metrics (NDCG, MRR, precision/recall)
Excellent problem-solving and analytical skills
Strong communication skills and ability to work in collaborative environments
Nice to Have:
Databases and Data Engineering for Big Data
Elasticsearch
Statistical Methods
Clearance:
Candidates should have an active clearance (secret/top secret, etc.) in order to be
considered for this position due to the nature of the work being done. Do not submit
candidates if they do not meet this requirement.
Work Location:
This position has the ability to work hybrid, remote or onsite. Please list which the
candidate prefers in the write up.
Interview Process:
1st round interview will be a Zoom with the hiring manager. 2nd round interview will be
a Zoom with additional team members as needed.
Must Have
Data/Reporting
Data Analysis 5 years
R, Python, SQL, and Machine Language Algorithms and Data Analysis. 5 years
Degree Level
Bachelors Degree Yes
Experience
Currently holds a Secret Clearance (OR a higher clearance) Yes
Quantitative relevancy analysis and tuning 5 years
Vector embeddings semantic search 5 years
Programming
C/C++, Java, Python, Bash, SQL, Java Script / HTML / CSS, Matlab 5 years
Software Tools
Apache Solr and creating data pipelines for search products 5 years
Nice to Have
Data/Reporting
Databases and Data Engineering for Big Data 0 years
Elasticsearch 0 years
Statistical Methods 0 years
Duration: 6 Months
Security Clearance Requirement: Yes
Security Clearance Level: Active Secret
Location: Lexington, MA 02421
Pay Range: $75-$100 an hour