Generative AI Engineer M/F
4 weeks ago
Position description
Category
OPERATIONS - ENGINEERING/PRODUCTION
Job title
Generative AI Engineer M/F
Contract
Permanent contract
Job description
Responsibilities:
Agent Development: Design and develop intelligent agents that can interact with users, understand complex tasks, and generate human like responses using LLMs and other AI techniques.
Custom LLM development: Finetune and customize existing LLMs or build new models from scratch to address specific business needs and domains.
Framework Expertise: Utilize and contribute to open-source or internal frameworks for LLM development, deployment, and management.
Application development: Build applications that leverage generative AI capabilities, including chatbots, text generation tools, code generation tools and more.
Deployment and Infrastructure: Deploy and manage AI services on AWS, ensuring scalability, reliability, and security.
Collaboration: Work closely with cross functional teams, including data scientists, software engineers, and product managers, to understand requirement and develop successful AI solutions.
Research and Development: Stay updated on latest advancements in generative AI and explore new technologies and techniques to improve the performance and capabilities of our AI systems.
Requirements:
Experience: 3-5 years of experience in developing and deploying AI solutions with a focus on generative AI and LLMs
LLMs: Strong understanding of LLM architectures, training models, and applications. Experience with popular LLMs such as GPT-4, Llama-2, Llama-3, Gemini or similar benchmark models.
Agent Frameworks: Proven ability to design and build intelligent agents using LLM and other AI techniques using Autogen, CrewAI, Autotrain, Langchain , Llama Index
Programming: Proficiency in Python and experience with deep learning libraries like TensorFlow or Pytorch.
Cloud computing: Experience with AWS services like EC2 , SageMaker, Lambda
Data pipeline technologies like Apache Kafka, AWS Kinesis and data storage solutions . ( S3 , Azure Blob Storage)
Knowledge of MLOps practices and tools (.: Kubeflow, MLFlow, SageMaker, Azure ML)
Rest API development using Flask or Django
Basic AI/ML skills
Python Libraries like Matplotlib, SciPy, Pandas
Pattern recognition using ML models, CNN, Time-Series modelling, and custom trained Transformer architectures.
Business Industry
Digital
Profile
Responsibilities:
Agent Development: Design and develop intelligent agents that can interact with users, understand complex tasks, and generate human like responses using LLMs and other AI techniques.
Custom LLM development: Finetune and customize existing LLMs or build new models from scratch to address specific business needs and domains.
Framework Expertise: Utilize and contribute to open-source or internal frameworks for LLM development, deployment, and management.
Application development: Build applications that leverage generative AI capabilities, including chatbots, text generation tools, code generation tools and more.
Deployment and Infrastructure: Deploy and manage AI services on AWS, ensuring scalability, reliability, and security.
Collaboration: Work closely with cross functional teams, including data scientists, software engineers, and product managers, to understand requirement and develop successful AI solutions.
Research and Development: Stay updated on latest advancements in generative AI and explore new technologies and techniques to improve the performance and capabilities of our AI systems.
Requirements:
Experience: 3-5 years of experience in developing and deploying AI solutions with a focus on generative AI and LLMs
LLMs: Strong understanding of LLM architectures, training models, and applications. Experience with popular LLMs such as GPT-4, Llama-2, Llama-3, Gemini or similar benchmark models.
Agent Frameworks: Proven ability to design and build intelligent agents using LLM and other AI techniques using Autogen, CrewAI, Autotrain, Langchain , Llama Index
Programming: Proficiency in Python and experience with deep learning libraries like TensorFlow or Pytorch.
Cloud computing: Experience with AWS services like EC2 , SageMaker, Lambda
Data pipeline technologies like Apache Kafka, AWS Kinesis and data storage solutions . ( S3 , Azure Blob Storage)
Knowledge of MLOps practices and tools (.: Kubeflow, MLFlow, SageMaker, Azure ML)
Rest API development using Flask or Django
Basic AI/ML skills
Python Libraries like Matplotlib, SciPy, Pandas
Pattern recognition using ML models, CNN, Time-Series modelling, and custom trained Transformer architectures.
Position location
Job location
Asia Pacific, India, Karnataka, Bangalore
Location
Bangalore
Candidate criteria
Level of experience
3 to 5 years
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