Assist in building and testing Generative AI demos and POCs
Support the design of simple scalable architectures for Generative AI applications
Work with team members to integrate AI components into larger systems
Use MLOps practices to help automate parts of the model development process
Follow guidelines to ensure that Generative AI applications are secure and meet basic governance standards
Help deploy AI applications on cloud platforms or on-premises setups with team support
Adapt to a fast-paced environment with evolving project needs
Keep up with AI trends and apply them to projects with guidance
Advise clients. Understand their needs analyze possible solutions and present the best options
Qualifications :
4 years of experience in IT industry with at least 2-3 years of experience in machine learning
Solid Back-end engineering skills particularly with Python (e.g. Django Flask or FastAPI).
Experience with pre-sales activities and opportunity processing
Basic experience with databases or tools like vector databases (e.g. Pinecone Weaviate Faiss)
Familiarity with AI frameworks such as TensorFlow PyTorch or Hugging Face
Understanding of CI/CD pipelines
Knowledge of RAG or AI application fundamentals (security governance etc.)
Experience with cloud platforms (AWS Google Cloud Azure) or on-premises setups
Ability to solve problems and handle shifting priorities with team support
Experience with client-facing roles
Ability to demonstrate ideas and solutions clearly and confidently
Bachelors or Masters degree in computer science machine learning artificial intelligence or a related field
Upper-Intermediate level of English
WOULD BE A PLUS
Knowledge of other programming languages such as Java or Go
Experience with open-source projects or exposure to tools such as Airflow or Spark
Familiarity with containers (e.g. Docker) or orchestration tools (e.g. Kubernetes)
Experience in the Banking and Financial Services domain
Experience with prompt engineering or fine-tuning LLMs
Remote Work :
Yes
Employment Type :
Full-time
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