Generative AI Engineer M/F
- Akkodis
- 3 - 5 years
- Bengaluru
- 1 year ago
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Job Description
- 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 e.g. ( S3 , Azure Blob Storage)
- Knowledge of MLOps practices and tools (e.g.: 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.
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 e.g. ( S3 , Azure Blob Storage)
- Knowledge of MLOps practices and tools (e.g.: 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.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Machine Learning EngineerEmployement Type: Full timeContact Details:
Company: AkkodisLocation(s): Bengaluru+ View Contact
Keyskills: Cloud computing Semiconductor SOC Django Application development Pattern recognition Apache Open source functional safety Python
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Akkodis
Akkodis is a global digital engineering company and Smart Industry leader. We enable clients to advance in their digital transformation with Talent, Academy, Consulting, and Solutions services. Our 50,000 experts combine best-in-class technologies, RD, and deep sector know-how for purposeful innovat...
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