AI Developer Part-Time

Engagement Details Our client is dedicated to advancing the security of AI and ML systems, providing comprehensive visibility and proactive protection to multi-modal systems, ensuring a safer, compliant, and resilient AI-powered future. We are seeking a highly skilled and experienced AI Developer to join our team. The ideal candidate will be responsible for helping our lead AI researcher build out our LLM guardrails, model evaluations systems, and ML Ops pipelines including dataset sing, normalization, and tool generation. In addition, you may be tasked with developing generative AI applications, including retrieval-augmented generation systems, chain-of-thought reasoning models, ReAct techniques, agents, and sophisticated chatbots for privacy-focused customers. Key Responsibilities Train And Fine-tune AI Models • Train best-use models to recognize security exploits. • Implement approaches in AI models to improve the detection of exploits. • Create AI agents for specific tasks like cybersecurity simulations based on fine-tuned LLMs. Development Of Tools For Synthetic Dataset Generation • Create AI tools specific to generating security exploits. Development Of Web Sers For Data Set Creation • Web sing of text and video for ingestion of content for continuous LLM fine-tuning using the latest exploits. Cybersecurity Simulations • Develop AI-driven cybersecurity agents capable of simulating various cybersecurity attacks for testing and training purposes. • Build Tools for Predictive Analytics: • Perform tasks related to predictive analytics, for fraud detection, or user behavior. Generative AI Development • Build advanced chatbots capable of understanding and answering queries based on large documents using private large language models. • Design and develop on top of models to enable real-time interactive AI security agents. • Develop and optimize retrieval-augmented generation (RAG) applications for industry-specific information retrieval use cases. DevOps And Backend Support • Ensure the smooth deployment and operation of AI models, including continuous integration and delivery (CI/CD), containerization, and cloud services management. What’s in it for you • Learn and evolve your skills using the latest and greatest technology tools in a rapidly growing company. • Learn from the best people around you. We constantly challenge the status quo and invent new ways of building a great product. • Flexible hours. Join daily standups, sprint planning, and retrospective meetings. Other than that you’re in control of your own schedule. • 100% remote. Work anywhere, whether it is remotely in the comfort of your home, in a shared co-working space, in an RV on the beach, or while being a nomad in another country. • Work on challenging problems, innovate, and positively impact many people's lives while having fun doing it. Required Qualifications • Upper-intermediate to fluent speaking and writing English. Able to have a real-time conversation. • 3+ years of full-time hands-on Software Development experience. • 2+ years of full-time hands-on JavaScript experience. • 2+ years of full-time hands-on Python backend (Django, FastAPI, Flask, asyncio, or similar) experience. • 1+ years of full-time hands-on AWS (or GCP, or Azure) experience. • 1+ years of full-time hands-on Docker or Kubernetes experience. • 0.5+ years of full-time hands-on AI Development experience. • Bachelor’s or greater degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. • A verifiable body of work with significant responsibility for the design and development of production AI and machine learning solutions. • Strong proficiency in programming languages Python, JavaScript. • Experience with generative AI models and fine-tuning techniques for models including GPT, LLAMA, Claude and other transformer models. • Proficient in using AI development tools and frameworks like TensorFlow, PyTorch, HuggingFace etc. • Experience with cloud platforms, and their AI offerings and the tradeoffs between them (GCP, Azure, AWS) • Knowledge of frameworks like LangChain, LlamaIndex, knowledge of their limitations, and ability to use them anyway. • Experience with containerization technologies (Docker, Kubernetes).