AI Engineer (Python Specialist with Ray and ML Expertise)

Position: AI Engineer (Python Specialist with Ray and ML Expertise)

Location: Austin, TX/Sunnyvale, CA (Onsite)

W2/C2C

Hands-on experience with RAY is mandate, profile will not work without it. 

Job Description:

We are looking for an experienced AI Engineer with strong Python skills and hands-on experience in distributed computing using Ray. This role involves designing, developing, and deploying advanced AI solutions, building scalable ML pipelines, and optimizing workflows for high-performance environments. The ideal candidate combines deep knowledge of AI algorithms, distributed systems, and exceptional programming skills.

Key Responsibilities:

• Design and implement AI/ML models leveraging frameworks like TensorFlow, PyTorch, and scikit-learn.
• Develop robust Python code for data preprocessing, feature engineering, model training, and deployment.
• Build and maintain end-to-end ML pipelines, ensuring scalability and reliability.
• Leverage Ray for distributed training and parallel processing to optimize performance across large datasets.
• Collaborate with data scientists, engineers, and product teams to deliver AI-driven solutions.
• Deploy AI models on cloud platforms (AWS, Azure, Google Cloud Platform) and apply MLOps best practices.
• Document algorithms, workflows, and code for maintainability and compliance.

Required Skills & Experience:

• Expert-level proficiency in Python and experience with AI/ML libraries (TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).
• Strong understanding of machine learning algorithms, deep learning architectures, and data processing techniques.
• Hands-on experience with Ray for distributed computing and scaling ML workloads.
• Experience with cloud AI services (AWS SageMaker, Azure ML, Google Cloud Platform AI).
• Familiarity with CI/CD pipelines, containerization (Docker, Kubernetes), and Infrastructure-as-Code tools (Terraform).
• Knowledge of SQL and NoSQL databases for data handling.
• Strong problem-solving and debugging skills.

Preferred Qualifications:

• Experience with Generative AI, LLMs, and prompt engineering.
• Knowledge of vector databases (FAISS, Pinecone) and RAG systems.
• Exposure to real-time AI systems, NLP, or computer vision.
• Contributions to open-source AI projects or published research.
• Cloud certifications (AWS, Azure, Google Cloud Platform) are a plus.