SQOR.ai · 14 hours ago
Co-Founder, Senior ML & AI Systems Engineer (LLM Optimization, NL2SQL, Agentic Systems, Python Expert) **Equity-based role**
United States
Full-time
Remote
Senior Level
7+ years expSQOR.ai is an AI-native Decision Intelligence platform that transforms business data into real-time, actionable insights. They are seeking a Senior ML & AI Systems Engineer to refine and scale machine learning and NLP systems, directly influencing the performance of their Decision Intelligence platform.
Artificial Intelligence (AI)B2BBusiness Information SystemsBusiness IntelligenceData IntegrationData VisualizationInformation TechnologyMachine LearningPredictive AnalyticsProductivity Tools
Hiring Manager
Laz Fuentes
Responsibilities
Optimize ML & NLP Systems for Decision Intelligence
Refine and deploy ML pipelines for accuracy, adaptability, and speed
Improve model performance, context handling, and retrieval mechanisms
Enhance inference efficiency using fine-tuning, quantization, and caching techniques
Collaborate closely with the Chief Data & AI Officer on continuous optimization and performance tracking
Evolve NL2SQL & Query Intelligence
Design and optimize natural language to SQL (NL2SQL) translation systems for dynamic query generation
Advance contextual query understanding across structured, semi-structured, and federated data
Develop schema-aware embedding and retrieval strategies that improve result precision and interpretability
Advance Agentic AI & Multi-Agent Architectures
Design and improve reasoning loops, context injection, and learning behaviors in multi-agent systems
Implement adaptive frameworks that enhance collaboration and task orchestration among agents
Work cross-functionally to ensure stability, performance, and adaptability in agent-driven analytics
System Performance & Scalability
Reduce latency and optimize system throughput for high-volume inference workloads
Implement distributed inference and load-balancing strategies for production scale
Collaborate with infrastructure engineers to ensure robustness, monitoring, and observability across ML and NLP pipelines
Qualification
Required
7+ years of experience designing and optimizing ML and NLP systems in production environments
Deep understanding of causal inference, predictive modeling, and time-series analysis
Proven expertise in fine-tuning and deploying large language models (LLMs) efficiently
Advanced proficiency in Python and frameworks such as LangChain, LangGraph, or AutoGen
Experience implementing RAG pipelines, NL2SQL systems, and semantic query interpreters
Familiarity with vector databases (Pinecone, Weaviate, or Vertex AI Matching Engine)
Strong grounding in microservice architectures, asynchronous messaging, and orchestration (GCP, Pub/Sub, Kubernetes)
Preferred
Experience building or optimizing conversational or decision-oriented AI systems
Familiarity with BI, analytics automation, or Decision Intelligence platforms
Knowledge of model evaluation frameworks and reinforcement learning from human or system feedback (RLHF/RLAIF)
Experience with embedding optimization, semantic search, or hybrid retrieval pipelines
Strong understanding of LLM performance trade-offs and multi-model routing
Benefits
Competitive equity
Long-term upside
Company
SQOR.ai
The future of Business Intelligence is not more dashboards. It is real-time answers.
11-50 employees
Funding
Current Stage
Early StageTotal Funding
$0.12MKey Investors
Techstars
2022-09-12Pre Seed· $0.12M
2022-01-09Non Equity Assistance
Leadership Team
Laz Fuentes
Founder and CEO
András Petery
Co-Founder and CCO
Recent News
2024-04-14
DBusiness Magazine
2023-01-14
Company data provided by crunchbase