About TableCheck
TableCheck is seeking a talented Machine Learning Engineer specializing in Search and Indexing to join our growing AI team. This role is critical in building and optimizing the search infrastructure that powers our platform's core capabilities.
Role Overview
We're looking for an experienced ML engineer who can bridge the gap between traditional search technologies and modern AI-powered solutions. You'll be responsible for designing, implementing, and optimizing search systems that combine the best of both worlds - leveraging classical information retrieval techniques alongside cutting-edge vector search and neural approaches.
Key Responsibilities
- Search Infrastructure Development
Design and implement scalable search systems combining traditional keyword-based and semantic vector search capabilities
Build and optimize hybrid search architectures that intelligently blend lexical and semantic matchingDevelop and maintain vector database solutions for efficient similarity search at scaleCreate robust indexing pipelines that handle real-time data ingestion and updatesModel Development and OptimizationFine-tune pre-trained language models for domain-specific search and retrieval tasks
Implement and optimize re-ranking models to improve search result relevanceBuild classification models for query understanding, intent detection, and result categorizationDevelop custom embedding models tailored to our specific use casesSearch Quality and PerformanceDesign and implement A / B testing frameworks for search improvements
Establish metrics and evaluation frameworks for search quality assessmentOptimize query latency and throughput while maintaining result qualityImplement caching strategies and performance optimizations for production systemsCollaboration and InnovationWork closely with product teams to understand search requirements and user needs
Collaborate with data scientists to integrate ML models into search pipelinesPartner with engineering teams to ensure smooth deployment and scalingStay current with latest developments in search technology and machine learningRequired Qualifications
Technical Expertise3+ years of experience building production search systems
Strong understanding of traditional search technologies (Elasticsearch, Solr, Lucene)Hands-on experience with vector databases (Pinecone, Weaviate, Milvus, Qdrant, or similar)Proven experience implementing hybrid search systems combining keyword and semantic searchExpertise in fine-tuning transformer models (BERT, RoBERTa, Sentence Transformers, etc.)Strong background in traditional ML techniques for ranking and classification (XGBoost, LightGBM, learning-to-rank)Experience with MLOps practices and model deployment pipelinesEducational Background3 years of experience or a bachelors degree in Computer Science, Machine Learning, or related field.
Nice-to-Have QualificationsExperience with multi-modal search (text, image, structured data)
Familiarity with query understanding and expansion techniquesExperience with personalized search and recommendation systemsContributions to open-source search or ML projects will be highly consideredWhat We Offer
Remote workOpportunity to work on challenging search problems at scaleCollaborative environment working directly with a full-stack team, talented engineers and data scientistsHow to Apply
If you're passionate about building intelligent search systems that combine the best of traditional and modern approaches, we'd love to hear from you. Please submit your resume containing a clear description of your most impactful search or ML project.
NOTE : This is a contract-only role and is not eligible for relocation.
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