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Job Title: AI Developer (Machine Learning / Generative AI)
Location: Palo Alto, CA
Duration: 12 Months
Employment Type: Contract
Job Summary
We are seeking a highly skilled AI Developer to design, build, and deploy scalable AI/ML solutions focused on data security, automation, and intelligent insights. The ideal candidate will have hands-on experience in machine learning, deep learning, and Generative AI, along with strong programming and cloud expertise.
Key Responsibilities
Job Title: AI Developer (Machine Learning / Generative AI)
Location: Palo Alto, CA
Duration: 12 Months
Employment Type: Contract
Job Summary
We are seeking a highly skilled AI Developer to design, build, and deploy scalable AI/ML solutions focused on data security, automation, and intelligent insights. The ideal candidate will have hands-on experience in machine learning, deep learning, and Generative AI, along with strong programming and cloud expertise.
Key Responsibilities
- Design, develop, and deploy machine learning and AI models for real-world business use cases
- Build and optimize Generative AI solutions (LLMs, NLP, RAG pipelines)
- Develop scalable data pipelines and model training workflows
- Collaborate with data engineers, product teams, and security teams to integrate AI solutions into enterprise platforms
- Work on data security, anomaly detection, and predictive analytics use cases
- Fine-tune pre-trained models and evaluate model performance
- Implement MLOps practices for model deployment, monitoring, and versioning
- Optimize models for performance, scalability, and cost efficiency
- Stay updated with latest advancements in AI/ML and apply best practices
- Strong experience in Python and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Hands-on experience with Generative AI, LLMs (OpenAI, Hugging Face, LangChain, RAG)
- Solid understanding of machine learning, deep learning, NLP, and data modeling
- Experience with cloud platforms (AWS, Azure, or Google Cloud Platform)
- Knowledge of data pipelines, ETL, and big data technologies
- Experience with model deployment, APIs, and microservices architecture
- Familiarity with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes)
- Strong problem-solving and analytical skills
- Experience in data security, backup, or cyber resilience domains
- Exposure to vector databases (Pinecone, FAISS, Weaviate)
- Experience building AI-powered enterprise applications