Head of Artificial Intelligence

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As 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 bonus
As 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 & Infrastructure
Oversee 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 & Mentorship
Hire 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 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.
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