Job Title

Senior NLP Engineer Location – BangaloreMode of work – work from officeExperience- 4+ yearsPosition SummaryWe're seeking a Senior NLP Engineer with a hacker mindset to revolutionize our information extraction engine for financial/legal data processing. This is a product-driven role focused on delivering production-ready solutions where accuracy and speed of output are paramount. Our systems are customer-facing with Human-in-the-Loop (HITL) workflows, requiring optimization for seamless human-AI collaboration. You'll have complete ownership from problem analysis to production deployment, leveraging any LLM, technique, or creative approach that delivers maximum accuracy in minimum time while ensuring optimal user experience.Key ResponsibilitiesCore Product-Driven AI WorkEnhance Information Extraction Engine: Redesign and optimize our current system using state-of-the-art LLMs for financial/legal document processing with focus on production accuracy and speedAccuracy Optimization: Achieve highest possible extraction accuracy through any means necessary—fine-tuning, prompt engineering, ensemble methods, or hybrid approachesLLM Integration: Implement and experiment with various LLMs (GPT, Claude, Llama, Gemini, etc.) to find optimal solutions for production useCreative Problem Solving: Think like a hacker—if traditional ML doesn't work, try prompt engineering, RAG, few-shot learning, or completely novel approachesLLM Development: Lead the pre-training and fine-tuning of large language models (LLMs) to optimize performance for specific financial/legal use casesInformation Retrieval, Extraction & Classification: Develop and implement techniques for retrieving, extracting, classifying, and ranking large-scale financial/legal datasets using advanced algorithms and vector databasesProduction-First Mindset: Every solution must be production-ready with measurable accuracy and performance metricsTime-to-Accuracy Optimization: Balance between achieving high accuracy and delivering results within acceptable time constraintsHuman-in-the-Loop (HITL) Workflow OptimizationHITL System Design: Build AI systems optimized for human review, correction, and validation workflowsConfidence Scoring & Routing: Develop intelligent routing systems that send low-confidence extractions to human reviewers while auto-approving high-confidence resultsInteractive Correction Interfaces: Design systems that learn from human corrections and feedback in real-timeWorkflow Efficiency: Optimize human review processes to minimize time spent while maximizing accuracy improvementsActive Learning Integration: Implement systems that strategically request human input on the most valuable data pointsFeedback Loop Optimization: Build mechanisms to continuously improve AI performance based on human corrections and preferencesUser Experience Design: Ensure seamless handoffs between AI processing and human review stagesEngineering ResponsibilitiesThird-Party LLM API Integration: Seamlessly integrate and manage multiple LLM APIs (OpenAI, Anthropic, Google, etc.) with fallback mechanismsAPI Development & Management: Build robust APIs for information extraction services with proper error handling and monitoringSystem Evaluation & Benchmarking: Develop comprehensive evaluation frameworks to measure accuracy, latency, and cost across different LLM approachesPerformance Engineering: Optimize systems for low-latency, high-throughput information extractionIntegration Architecture: Build seamless integrations with existing financial/legal data workflows and customer systemsEnd-to-End Product DeliveryComplete Product Ownership: Take problems from customer requirements through development, testing, and production deploymentQuality Assurance: Ensure production systems maintain consistent accuracy and reliability standardsRapid Iteration: Quickly implement user feedback and production improvementsStartup Engineering MindsetEngineering-First Approach: Prioritize engineering solutions that work in production over theoretical researchPragmatic Decision Making: Choose solutions based on production requirements, not academic interestResource Optimization: Balance accuracy, speed, and cost for optimal business outcomesScalability Focus: Build systems that can handle increasing data volumes and customer demandsIntegration Expertise: Excel at connecting different systems, APIs, and data sourcesRequired QualificationsExperience & Background4-8 years of Applied AI/ML experience with production deployments and customer-facing productsHITL System Experience: Hands-on experience building Human-in-the-Loop AI systems and workflowsProduction LLM Experience: Hands-on experience integrating and productionizing LLM solutions, not just researchInformation Extraction in Production: Proven track record of deploying IE systems that serve real business needsAPI Integration Expertise: Experience working with third-party APIs, handling rate limits, errors, and failoversTechnical SkillsProgramming: Expert in Python with strong software engineering practicesProduction LLM Techniques:Pre-training and fine-tuning of large language modelsAPI integration and management (OpenAI, Anthropic, Google, etc.)Prompt engineering for production accuracyModel evaluation and benchmarkingCost optimization and performance tuningInformation Retrieval: Vector databases, ranking algorithms, search systemsEngineering Frameworks: FastAPI, Flask, Docker, Kubernetes, cloud servicesQuality Assurance: Multi-stage review processes, validation workflows, error detectionCritical Product MindsetCustomer-Centric: Focus on optimizing the end-user experience in human-AI collaborative workflowsWorkflow Optimization: Understand and improve human work patterns and efficiencyProduction-First: Every solution must work reliably in customer-facing environmentsUser Trust: Build systems that maintain and enhance user confidence in AI outputsIterative Improvement: Design systems that get better through human interactionQuality Obsession: Maintain high standards for both AI accuracy and user experienceDaily activities include:Monitoring production systems and addressing any issuesAnalyzing user feedback and correction patterns from support ticketsCode reviews and preparing for weekly releasesCollaborating with product and internal teamsIncremental improvements to existing workflowsTesting and evaluating changes through internal metrics before weekly deploymentPlanning and scoping work for upcoming weekly releasesEngineering scenarios you'll handle:API rate limiting and failover logic when OpenAI is downBuilding custom evaluation metrics for financial/legal document accuracyOptimizing prompt costs while maintaining extraction qualityDebugging production issues affecting customer workflowsIntegrating with customer systems and data formatsSuccess MetricsProduction Accuracy: Measurable improvement in extraction precision/recall in live systemsAutomation Rate: Percentage of extractions that can be auto-approved without human reviewCost Efficiency: Optimal balance of accuracy, speed, and LLM API costsTime to Production: Speed from problem identification to deployed solutionThis Role is NOT For You If:You prefer research over production implementationYou want to publish papers rather than ship productsYou need perfect data or requirements before startingYou're more interested in novel algorithms than customer problemsYou avoid the "messy" work of production systems and integrationsThis Role IS Perfect For You If:You love seeing your AI solutions used by real customersYou get excited about optimizing production systems for accuracy and speedYou enjoy the engineering challenges of integrating multiple LLM APIsYou measure success by customer outcomes, not research metricsYou thrive on solving practical problems with whatever works bestYou take pride in building reliable, scalable production systems How to Apply:Please send your resume and portfolio to We Are-Alphastream.ai envisions a dynamicfuture for the financial world, where innovation is propelled by state-of-the-art AI technology and enriched by a profound understanding of credit and fixed- income research. Our mission is to empowerasset managers, researchfirms, hedge funds,banks, and investors with smarter, faster, and curated data. We provide accurate, timely information, analytics, and tools across simple to complex financial and non-financial data, enhancing decision- making. With a focus on bonds, loans, financials and sustainability, we offer near real-time data via APIs and PaaS (Platform as a Service) solutions that act as the bridge between our offerings and seamless workflow integration.To learn more about us: is an equal opportunity employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of all communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a cultureof inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.