AI Developer (Machine Learning / Generative AI)
Aziro Technologies Llc
Palo Alto, United States of America
yesterday
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Palo Alto, United States of America
Tech stack
API
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Big Data
Computer Programming
ETL
Data Security
Python
Machine Learning
Natural Language Processing
Cloud Services
TensorFlow
Management of Software Versions
Google Cloud Platform
Enterprise Software Applications
PyTorch
Large Language Models
Deep Learning
Generative AI
Scikit Learn
Kubernetes
HuggingFace
Machine Learning Operations
Data Pipelines
Docker
Microservices
Job description
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., * 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
Requirements
- 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