Role AI Engineer.
Role:
Conduct cuttingedge research in Multimodal pretrained models and NLP focusing on document understanding and intelligence.
Develop and implement groundbreaking techniques in LLM and Generative AI.
Develop ProofofConcept (POC) projects to validate innovative ideas.
Create ML models aligned with business objectives ensuring data quality and model accuracy.
Engage in data preparation cleaning and verification for optimal model training.
Finetune models and adjust hyperparameters for peak performance.
Deploy models integrate them within business applications and embed them in business processes.
Collaborate with testing engineers to construct test cases for model validation.
Enhance MLOps toolkits for efficient machine learning lifecycle management.
Requirements:
Familiarity with cloud platforms (e.g. AWS Azure Google Cloud StreamLit) and AI services.
Advanced degree (Masters or Bachelors) in Machine Learning NLP Computer Science Data Science Statistics or related fields.
Expertise in Multimodal Representation Learning Gen AI/LLM NLP.
Proficiency in Python and familiarity with ML frameworks like PyTorch.
Experience in document understanding/intelligence is highly advantageous.
Knowledge of MLOps and ML Model Lifecycle Management.
Exceptional analytical problemsolving and communication skills.
Ability to work under pressure show initiative and rapidly adapt to new challenges.
Eagerness to collaborate with international teams.
aws,ml models,azure,ml model lifecycle management,ml frameworks,models,communication skills,nlp,data preparation,streamlit,llm,machine learning lifecycle management,problem-solving skills,multimodal pre-trained models,generative ai,python,management,data science,analytical skills,model training,machine learning,google cloud,mlops,cloud platforms,document understanding/intelligence,ai fundamentals,statistics,mlops toolkits