[Remote] Co-Founder, Senior ML & AI Systems Engineer (LLM Optimization, NL2SQL, Agentic Systems, Python Expert) **Equity-based role**

Note: The job is a remote job and is open to candidates in USA. SQOR.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. 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 Skills • 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) • 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 Overview • The future of Business Intelligence is not more dashboards. It is real-time answers. It was founded in 2021, and is headquartered in New York, New York, USA, with a workforce of 11-50 employees. Its website is Apply tot his job