Cynet systems Inc
AI Developer - Remote / Telecommute
Cynet systems Inc, Pleasanton, California, United States, 94566
Overview
Pay Range: $65hr - $70hr
Responsibilities
Architect and design end-to-end generative AI solutions (text, image, audio, or multimodal) that align with business objectives.
Evaluate and select appropriate foundation models (e.g., GPT, LLaMA, Stable Diffusion) and fine-tuning strategies.
Lead the development of custom LLM applications, including prompt engineering, fine-tuning, RLHF, and model compression.
Collaborate with cross-functional teams (engineering, product, design, data science) to integrate AI into products and platforms.
Ensure responsible and ethical AI practices are embedded in system design (e.g., fairness, privacy, explainability).
Guide the implementation of AI infrastructure (data pipelines, vector databases, model serving, APIs).
Stay up-to-date on the latest AI research and tools, and make recommendations for adoption.
Conduct proofs-of-concept, prototypes, and performance benchmarking.
Mentor junior engineers and contribute to best practices and internal knowledge sharing.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning
7+ years of experience in AI/ML, with 3+ years in generative AI (LLMs, diffusion models, etc.).
Proven experience designing and deploying large-scale AI systems.
Deep understanding of transformer architectures, tokenization, and pretraining/fine-tuning paradigms.
Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, etc.
Strong knowledge of MLOps, cloud platforms (AWS, GCP, Azure), and scalable architectures (e.g., microservices, serverless).
Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) systems.
Familiarity with responsible AI frameworks and privacy-preserving techniques.
Preferred Qualifications
Experience with open-source LLMs and model distillation/quantization techniques.
Exposure to multimodal AI models (e.g., CLIP, DALL·E, Imagen).
Contributions to AI/ML research (e.g., published papers, open-source projects).
Experience building GenAI copilots, chatbots, or productivity tools.
Soft Skills
Strong problem-solving and analytical skills.
Excellent communication and stakeholder management abilities.
Ability to translate complex AI concepts into business value.
Entrepreneurial mindset and passion for innovation.
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Responsibilities
Architect and design end-to-end generative AI solutions (text, image, audio, or multimodal) that align with business objectives.
Evaluate and select appropriate foundation models (e.g., GPT, LLaMA, Stable Diffusion) and fine-tuning strategies.
Lead the development of custom LLM applications, including prompt engineering, fine-tuning, RLHF, and model compression.
Collaborate with cross-functional teams (engineering, product, design, data science) to integrate AI into products and platforms.
Ensure responsible and ethical AI practices are embedded in system design (e.g., fairness, privacy, explainability).
Guide the implementation of AI infrastructure (data pipelines, vector databases, model serving, APIs).
Stay up-to-date on the latest AI research and tools, and make recommendations for adoption.
Conduct proofs-of-concept, prototypes, and performance benchmarking.
Mentor junior engineers and contribute to best practices and internal knowledge sharing.
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning
7+ years of experience in AI/ML, with 3+ years in generative AI (LLMs, diffusion models, etc.).
Proven experience designing and deploying large-scale AI systems.
Deep understanding of transformer architectures, tokenization, and pretraining/fine-tuning paradigms.
Hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, LangChain, etc.
Strong knowledge of MLOps, cloud platforms (AWS, GCP, Azure), and scalable architectures (e.g., microservices, serverless).
Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) systems.
Familiarity with responsible AI frameworks and privacy-preserving techniques.
Preferred Qualifications
Experience with open-source LLMs and model distillation/quantization techniques.
Exposure to multimodal AI models (e.g., CLIP, DALL·E, Imagen).
Contributions to AI/ML research (e.g., published papers, open-source projects).
Experience building GenAI copilots, chatbots, or productivity tools.
Soft Skills
Strong problem-solving and analytical skills.
Excellent communication and stakeholder management abilities.
Ability to translate complex AI concepts into business value.
Entrepreneurial mindset and passion for innovation.
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