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Head of AI

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Scrumconnect ConsultingAs Head of AI, you will be the primary technical driver of all AI/ML initiatives. Youll report directly to the CEO/CTO and own the full lifecycle of our AI roadmapfrom research and proof-of-concept to scalable production. Were looking for a doer who can rapidly prototype models, optimize for performance, and mentor junior engineers, all while helping define product strategy. Lead AI strategy and execution in a high-ambiguity environment.deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures).Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring.Collaborate closely with product, design, and DevOps to integrate AI features into our platform.Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round.Salary- 90k-100k, plus 25k bonusAs Head of AI, you will be the primary technical driver of all AI/ML initiatives. Youll report directly to the CEO/CTO and own the full lifecycle of our AI roadmapfrom research and proof-of-concept to scalable production. Were looking for a doer who can rapidly prototype models, optimize for performance, and mentor junior engineers, all while helping define product strategy. Lead AI strategy and execution in a high-ambiguity environment.deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures).Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring.Collaborate closely with product, design, and DevOps to integrate AI features into our platform.Recruit, mentor, and grow an AI/ML team as we scale beyond our seed round.

Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference.neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent.Productionize models in cloud/on-prem environments (AWS/GCP/Azure) with containerization (Docker/Kubernetes) and ensure low-latency, high-availability inference.Develop a multi-quarter AI roadmap aligned with product milestones and fundraising milestones.Identify and evaluate opportunities for AI-driven competitive advantages (e.g., proprietary data, unique model architectures, transfer/few-shot learning).Collaborate with business stakeholders to translate big problems into technically feasible AI solutions.Data and InfrastructureOversee the creation and maintenance of scalable data pipelines (ETL/ELT) and data lakes/warehouses.Establish best practices for data labeling, versioning, and governance to ensure high data quality.Implement ML Ops processes: CI/CD for model training, automated testing, modeldrift detection, and continuous monitoring.Team Building and MentorshipHire and mentor AI/ML engineers, data scientists, and research interns.Set coding standards, model-development guidelines, and rigor around reproducible experiments (e.g., Stay abreast of state-of-the-art AI research (e.g., pre-training, fine-tuning, generative methods) and evaluate applicability.Forge partnerships with academic labs or open-source communities to accelerate innovation.

Demonstrated track record of shipping AI/ML products end-to-end (from prototype to production).Hands-on expertise building and deploying deep learning models (e.g., CNNs, Transformers, graph neural networks) in real-world applications.Proficiency in Python and core ML libraries (PyTorch, TensorFlow, scikit-learn, Hugging Face, etc.).Strong software engineering background: data structures, algorithms, distributed systems, and version control (Git).Experience designing scalable ML infrastructure on cloud platforms (AWS SageMaker, GCP AI Platform, Azure ML, or equivalent).Solid understanding of data-engineering concepts: SQL/noSQL, data pipelines (Airflow, Prefect, or similar), and batch/streaming frameworks (Spark, Kafka).Experience recruiting and mentoring engineers or data scientists in a fast-paced environment.Bachelors or Masters in Computer Science, AI/ML, Electrical Engineering, Statistics, or a related field. (D. in AI/ML is a plus but not required if hands-on experience is extensive.)

Prior experience in a stealth-mode or early-stage startup, ideally taking an AI product from 0 1.healthcare AI, autonomous systems, finance, robotics, computer vision, or NLP).Hands-on experience with large-scale language models (LLMs) and prompt engineering (e.g., Familiarity with on-device or edge-AI deployments (e.g., Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL, etc.).

Bias for Action: You favor shipping an MVP quickly, measuring impact, and iteratingover striving for perfect academic proofs that never see production.Ownership Mentality: You treat the startup as your own: you take responsibility for system uptime, data integrity, and feature adoption, not just model accuracy.Collaborative Attitude: You value cross-functional teamwork and can pivot between researcher mode and software engineer mode depending on the task at hand.Competitive Compensation: Youll shape the technical direction of our AI stack and lay the groundwork for a market-leading product.Flexible Work Environment: Remote-friendly with occasional in-person retreats or team meetups.Fast-Track Growth: As our first AI hire and eventual team leader, youll rapidly expand your responsibilitiesand the team you buildwithin months.

Please send your resume/CV and a brief cover letter to jobs@stealth-ai.Head of AI Application [Your Name]A recent project where you built and deployed an AI/ML system end-to-end (include technical stack and impact).Any leadership or mentoring experience guiding other engineers or data scientists.We are committed to building a diverse team and welcome applicants of all backgrounds. Ready to build world-class AI from day one? Come join us and help shape the future.career-website-detail-template-2 =