What are the responsibilities and job description for the AI Engineer (Python Specialist with Ray and ML Expertise) position at HPTech Inc.?
Job Details
Please Note: There are two locations Austin, TX/Sunnyvale, CA (Onsite)
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.
Cygnus Diversity, Inclusion & Equal Opportunity Commitment
We proudly promote equal opportunities and inclusive workplaces. All employment decisions are based on qualifications and project needs.
We proudly promote equal opportunities and inclusive workplaces. All employment decisions are based on qualifications and project needs.
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