AIML hands on Agentic AI Gen AI Usage of LLM Creating Agents CI/CD understanding Backend (NodeJS NextJS Java) and Front end (ReactJS) understanding Connecting LLM with Azure etc.
5 years of AI/ML Expertise: Understanding of core AI and machine learning concepts models and algorithms demonstrated through practical application and system design. Ability to explain complex ideas clearly and significant focus on building and deploying production-grade AI/ML models and systems
LLM Experience: Hands-on experience building applications leveraging LLMs and deploying them into a production environment (considering aspects like performance cost reliability monitoring) Workflows and Agentic AI
Solid Engineering Fundamentals: Proven growth in software design data structures algorithms and writing clean testable and maintainable code
Technical Breadth:
Familiarity and hands-on experience with relevant technologies/frameworks like Databricks Azure AI Azure Transcription Services RLlib (Agent Model) PyTorch(State Model) Open AI GCP
backend services(e.g.
cloud platforms (AWS/GCP/Azure)
front-end frameworks (e.g. React/React Native)
CI/CD pipelines REST/WebSocket API development and database technologies.
Solid programming skills in Python with experience in pandas numpy and SQL proficiency in frameworks such as Scikit Learn TensorFlow and PyTorch
Broaden ML Domain Knowledge: Practical experience or solid knowledge in various machine learning domains such as Natural Language Processing (NLP) Computer Vision Personalization & Recommendation systems and/or Anomaly Detection
Adaptability & Learning Agility: Proven ability to quickly learn new technologies and methodologies comfortable working on tasks requiring exploration and tackling ambiguity
Ownership & Drive: Self-driven takes immense pride in technical contributions proactively tackle problems own features end-to-end and find satisfaction in building impactful solutions
Inherent Curiosity: Has a solid desire to understand *how* and *why* things work driving the what to build better more efficient systems
AIML hands on Agentic AI Gen AI Usage of LLM Creating Agents CI/CD understanding Backend (NodeJS NextJS Java) and Front end (ReactJS) understanding Connecting LLM with Azure etc. 5 years of AI/ML Expertise: Understanding of core AI and machine learning concepts models and algorithms demonstrated thr...
AIML hands on Agentic AI Gen AI Usage of LLM Creating Agents CI/CD understanding Backend (NodeJS NextJS Java) and Front end (ReactJS) understanding Connecting LLM with Azure etc.
5 years of AI/ML Expertise: Understanding of core AI and machine learning concepts models and algorithms demonstrated through practical application and system design. Ability to explain complex ideas clearly and significant focus on building and deploying production-grade AI/ML models and systems
LLM Experience: Hands-on experience building applications leveraging LLMs and deploying them into a production environment (considering aspects like performance cost reliability monitoring) Workflows and Agentic AI
Solid Engineering Fundamentals: Proven growth in software design data structures algorithms and writing clean testable and maintainable code
Technical Breadth:
Familiarity and hands-on experience with relevant technologies/frameworks like Databricks Azure AI Azure Transcription Services RLlib (Agent Model) PyTorch(State Model) Open AI GCP
backend services(e.g.
cloud platforms (AWS/GCP/Azure)
front-end frameworks (e.g. React/React Native)
CI/CD pipelines REST/WebSocket API development and database technologies.
Solid programming skills in Python with experience in pandas numpy and SQL proficiency in frameworks such as Scikit Learn TensorFlow and PyTorch
Broaden ML Domain Knowledge: Practical experience or solid knowledge in various machine learning domains such as Natural Language Processing (NLP) Computer Vision Personalization & Recommendation systems and/or Anomaly Detection
Adaptability & Learning Agility: Proven ability to quickly learn new technologies and methodologies comfortable working on tasks requiring exploration and tackling ambiguity
Ownership & Drive: Self-driven takes immense pride in technical contributions proactively tackle problems own features end-to-end and find satisfaction in building impactful solutions
Inherent Curiosity: Has a solid desire to understand *how* and *why* things work driving the what to build better more efficient systems
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