AI Developer (Python)

<p>This is a remote position.</p> <b>SUMMARY</b> <br> The <b>AI Developer (Python)</b> role focuses on designing, developing, and optimizing AI/ML solutions in local-first environments, prioritizing data security, offline accessibility, and system autonomy. This role is ideal for a Python developer with a deep understanding of embedded storage systems, offline inference, and graph-based data models, who thrives in non-cloud, privacy-focused setups. The ideal candidate brings hands-on expertise in model training, local storage, and graph computation—supporting projects that require powerful offline data science solutions.<br> <br> <b>JOB RESPONSIBILITIES</b><b><br></b>
<ul>
<li>Design and implement AI/ML pipelines using Python with local storage architecture.<br></li>
<li>Handle local model training, versioning, optimization, and offline inference using frameworks such as scikit-learn, XGBoost, LightGBM, and optionally PyTorch or TensorFlow.<br></li>
<li>Store and process data using SQLite, DuckDB, and flat file formats (CSV, JSON, Parquet, Pickle).<br></li>
<li>Manage secure local model and data caching for privacy-compliant workflows.<br></li>
<li>Build and manage local graph databases using Neo4j Community Edition, applying Cypher queries for relationship analysis and entity resolution.<br></li>
<li>Implement dimensionality reduction techniques such as PCA, t-SNE, or UMAP to streamline local ML performance.<br></li>
<li>Ensure secure handling of sensitive data using encrypted local storage, with awareness of HIPAA, GDPR, and other compliance standards.<br></li>
<li>Automate offline AI workflows using Python scripting, cron jobs, or Windows Task Scheduler.<br></li>
<li>Document development processes, model lifecycle, and preprocessing techniques.<br></li>
<li>(Optional) Develop lightweight local web interfaces with Flask or FastAPI.<br></li>
<li>(Optional) Deploy models on edge devices like Raspberry Pi or Jetson Nano.<br></li>
</ul> <br> <b>QUALIFICATIONS</b><br>
<ul>
<li>Bachelor’s degree in Computer Science, Data Science, Engineering, or equivalent work experience.<br></li>
<li>5+ years of Python development experience, with strong skills in writing clean, modular code.<br></li>
<li><b>Proven experience with:</b><b><br></b></li>
</ul>
<ul>
<li>scikit-learn, XGBoost, LightGBM.<br></li>
<li>Local-first data workflows and embedded DBs (SQLite, DuckDB).<br></li>
<li>Local model saving/loading with joblib, pickle, torch.save, etc.<br></li>
<li>Neo4j graph database and Cypher query language.<br></li>
<li>Secure offline environments without external API dependencies.<br></li>
</ul>
<ul>
<li><b>Strong understanding of:</b><b><br></b></li>
</ul>
<ul>
<li>Data preprocessing (handling nulls, normalization, feature engineering).<br></li>
<li>Local model inference optimization (CPU/GPU).<br></li>
<li>Data privacy regulations (HIPAA, GDPR).<br></li>
</ul>
<ul>
<li>Git version control.<br></li>
<li>Proficiency with Python scripting for automation.<br></li>
<li>Comfort working in cloud-disconnected environments.<br></li>
<li>Bonus: Experience with NetworkX, ArangoDB, Dgraph, or graph-tool.<br></li>
<li>Bonus: Background in edge/IoT AI deployment.<br></li>
</ul> <br> <b>JOB REQUIREMENTS</b><b><br></b>
<ul>
<li>Should be willing to accept a long-term work-from-home arrangement.<br></li>
<li>Should be amenable to a permanent night shift schedule.<br></li>
</ul><br>