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CTO, Co-Founder, Predictive Brand Intelligence Venture | Pre-Seed | Equity-Only jobs in United States
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NeedTech Labs · 2 weeks ago

CTO, Co-Founder, Predictive Brand Intelligence Venture | Pre-Seed | Equity-Only

NeedTech Labs is a stealth-mode predictive brand intelligence venture building a patent-pending AI platform for enterprise brand analytics. The CTO & Co-Founder will own the full technical roadmap and lead the development of a production-grade, enterprise-deployable asset focused on anticipatory brand sentiment forecasting.
MarketplacePublishingSaaSOnline Portals
Hiring Manager
Daniel Katz
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Responsibilities

Own the end-to-end technical roadmap from MVP through production scale, spanning multimodal ingestion, temporal deep learning models, scenario simulation engine, and cloud-native platform architecture
Architect the multimodal data ingestion layer : social platform APIs, news and media feeds, financial data feeds, review and forum sources, and structured enterprise data — with normalization, deduplication, and real-time streaming discipline across heterogeneous, high-velocity sources
Architect the temporal deep learning core : sequence models (transformers, temporal convolutional networks, state-space models) for longitudinal sentiment dynamics, crisis event detection and classification in context, anomaly detection tuned to cyclical market phenomena, and exogenous shock modeling
Architect the real-time scenario analysis engine : forward-looking simulation of sentiment trajectories under alternative conditions, uncertainty quantification, and the modeling discipline that separates genuine forecasting from retrospective trend-fitting
Design the continuous learning and modality-expansion architecture : online/incremental learning pipelines that adapt to new data and volatile market conditions without full retraining, and a plug-and-play framework for adding new data modalities without re-architecting the core model
Lead the cloud-native platform architecture: Kubernetes, Docker, Terraform IaC, multi-region auto-scaling, streaming data infrastructure (Kafka or equivalent), and observability tooling appropriate to real-time enterprise dashboards
Lead data compliance and licensing architecture: GDPR-compliant data sourcing, platform API terms-of-service adherence across social and news data sources, and SOC 2 Type II readiness for enterprise and financial services buyers
Drive IP execution: continuation filings, claim-chart development around the multimodal temporal sentiment forecasting claim space, prior-art analysis against Brandwatch, Talkwalker, and Zignal Labs, and trade-secret architecture around model training and modality-expansion design
Lead technical engagement with design-partner enterprises, validating forecast accuracy and early-warning lead-time against real-world crisis and market events
Build and lead the founding technical team across ML engineering, data engineering, NLP, platform engineering, and applications engineering
Serve as the principal technical voice in investor diligence, enterprise customer technical due diligence, and strategic partnership conversations

Qualification

Multimodal machine learningTemporal deep learning architecturesTransformersRNN/LSTM variantsTemporal convolutional networksState-space modelsTime-series forecastingAnomaly detectionMultimodal data fusionCloud-native infrastructureKubernetesDockerTerraformStreaming data pipelinesKafkaMulti-region auto-scalingHigh-volume data ingestionSocial platform APIsNews platform APIsOnline/incremental learningModel retraining disciplineData licensing constraintsPlatform API terms-of-serviceNLPFinancial time-series modelingCrisis event detection systemsEnterprise dashboard delivery

Required

8+ years shipping production ML/AI systems at scale, with substantive experience in NLP, time-series forecasting, or multimodal machine learning categories
Direct production experience with temporal/sequential deep learning architectures — transformers, RNN/LSTM variants, temporal convolutional networks, or state-space models — applied to forecasting or anomaly detection at scale. Research-only exposure without production shipping is not qualified
Direct production experience with multimodal data fusion — combining text, structured, and time-series signals into a unified modeling substrate. Single-modality NLP experience alone is not qualified
Demonstrable architectural fluency across cloud-native infrastructure: Kubernetes, Docker, Terraform, streaming data pipelines (Kafka or equivalent), and multi-region auto-scaling
Direct experience with high-volume, high-velocity data ingestion from heterogeneous external sources, including social and news platform APIs
Working experience with online/incremental learning and model retraining discipline appropriate to volatile, non-stationary data environments
Zero-to-one leadership track record: a prior CTO, founding engineer, or technical lead role at an AI/ML SaaS venture, taking technology from architectural design through production deployment
Working familiarity with data licensing constraints and platform API terms-of-service considerations relevant to social and news data aggregation at scale
Graduate degree (Ph.D. preferred) in computer science, machine learning, computational linguistics, statistics, or adjacent field

Preferred

Prior exit (acquisition or IPO) as a technical founder or early technical leader in social listening, brand analytics, or NLP/forecasting SaaS — Brandwatch (Cision), Talkwalker, Meltwater, Zignal Labs, NetBase Quid, or comparable lineage
Direct operating experience inside a tier-one communications, martech, or financial data corporate (Cision, Meltwater, Bloomberg, FactSet)
Named inventor on granted patents in multimodal machine learning, temporal forecasting, or sentiment analysis methodologies
Published or patent-cited record in NeurIPS, ICML, ACL, EMNLP, KDD, or equivalent venues, particularly in time-series forecasting, multimodal fusion, or applied NLP
Hands-on experience with financial time-series modeling or market-signal forecasting, given the investor relations and financial sentiment monitoring use case
Operating familiarity with crisis event detection systems and the practical engineering of low-false-positive anomaly detection in noisy, high-volume social data
Experience architecting systems for enterprise dashboard delivery with strict latency and reliability requirements

Benefits

Co-Founder equity. Material, vesting on standard terms with appropriate cliff and acceleration.
Founder-level participation in subsequent funding rounds.

Company

NeedTech Labs

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NeedTech Labs is an AI-first venture platform that aims to revolutionize startup development.

Funding

Current Stage
Early Stage

Leadership Team

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Daniel Katz
Co-Founder & CEO
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Shalom Daskal
Chairman Co-Founder NeedTech Labs
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Company data provided by crunchbase