Lead AI Systems & LLMs for Scale (Remote)

AlgoLand is a global AI advisory and product company specializing in applied artificial intelligence, advanced analytics, and scalable AI systems. We partner with enterprises and governments to design, build, and deploy AI solutions that generate measurable business impact. Our work spans optimization, machine learning, and next-generation AI systems, including large language models (LLMs) and autonomous agents.We operate at the intersection of science and business, translating cutting-edge research into production-grade systems used in real-world environments. Our culture emphasizes technical excellence, ownership, and outcome-driven delivery.Role OverviewWe are seeking a Lead Applied AI Scientist to drive the design, development, and deployment of AI solutions at scale. This is a senior, hands-on leadership role combining deep technical expertise with system-level thinking and product impact.You will lead end-to-end AI initiatives—from problem framing and modeling to deployment and continuous optimization—across a range of use cases including predictive modeling, optimization, and LLM-based systems.This is a fully remote role, operating within a distributed team. Availability in or close to GCC time zones is strongly preferred to ensure alignment with clients and delivery teams.Key Responsibilities1. AI System Design & DevelopmentLead the design and implementation of advanced AI models across domains (forecasting, optimization, classification, recommendation, etc.)Architect scalable AI pipelines, from data ingestion to model servingApply statistical modeling, machine learning, and deep learning techniques to solve complex business problemsTranslate ambiguous business challenges into structured AI solutions with clear success criteria2. LLMs and Next-Gen AI SystemsDesign and deploy LLM-based solutions (RAG pipelines, fine-tuning, prompt engineering, agentic workflows)Evaluate and optimize LLM performance (latency, accuracy, cost, hallucination control)Build domain-specific AI systems leveraging proprietary data and custom modelsStay at the forefront of advancements in generative AI and integrate them into production systemsLead deployment of AI models into production environments at scale (cloud or on-prem)Define and implement MLOps best practices (CI/CD, monitoring, retraining, versioning)Ensure reliability, scalability, and performance of AI systems (latency, throughput, robustness)Work closely with engineering teams to integrate models into business workflows and applications4. Technical LeadershipProvide technical direction and mentorship to AI scientists and engineersEstablish standards for model development, evaluation, and deploymentReview and challenge model design, assumptions, and methodologies to ensure rigorContribute to building reusable frameworks, accelerators, and internal tooling5. Client & Stakeholder EngagementCollaborate with business stakeholders to define AI use cases and expected impactCommunicate complex AI concepts clearly to non-technical audiences (executives, product teams)Support proposal development, solution design, and technical positioning in client engagementsQualificationsRequiredAdvanced degree (Master’s or PhD) in Computer Science, Data Science, Applied Mathematics, or related field6–10+ years of experience in applied AI / machine learning roles, with demonstrated production impactStrong expertise in:Machine Learning and Statistical ModelingData modeling and feature engineeringProven experience deploying AI models into production at scaleStrong programming skills (Python required; additional languages are a plus)Experience with modern data and ML ecosystems (e.g., MLflow, Docker, Kubernetes, cloud platforms)Solid understanding of model evaluation, validation, and performance monitoringBasic understanding of Cloud technologiesPreferredExperience with LLMs and Generative AI systems (RAG, fine-tuning, embeddings, agents)Experience in optimization / operations research is a strong plusFamiliarity with distributed systems and high-scale data pipelinesExposure to multiple industries (retail, telecom, finance, etc.)Experience working in consulting or client-facing environmentsGCP knowledgeStrong problem-solving ability with a structured, scientific approachAbility to operate autonomously in a remote, distributed environmentOwnership mindset: from concept to productionHigh standards of rigor, with attention to reproducibility and reliabilityClear and concise communication, both technical and business-orientedFully remote, globally distributed teamHigh degree of autonomy and ownership expectedAsync-first collaboration culture with strong documentation practicesFast-paced, outcome-driven environment focused on real-world impactPreference for candidates aligned with GCC time zones to support client collaborationWhat We OfferOpportunity to work on high-impact AI problems across industriesExposure to cutting-edge AI technologies, including LLMs and advanced optimizationA culture of