Software Engineer (AI/ML)
Tasks
- Build and fine-tune LLMs
- Build vector database and semantic search solutions
- Conduct RAG research
- Create conversational AI applications
- Deploy ML models to cloud or on prem systems
- Design generative AI models
- Develop NLP algorithms
- Evaluate model performance with testing frameworks
- Implement chatbots and virtual assistants
- Implement prompt engineering
- Integrate NLP and GenAI into production pipelines
- Process and analyze large datasets
- Research emerging ML and NLP techniques
- Train deep learning models
- Tune hyperparameters to optimize performance
Perks/Benefits
- Birthday day off
- Career advancement
- Employee assistance program
- Gratuity
- Group personal accident insurance
- Group term life insurance
- Learning and development opportunities
- Maternity leave
- Medical insurance
- Paid Holidays
- Paid casual leave
- Paid sick leave
- Paternity leave
- Privilege leaves
- Provident fund
- Work-life balance
Skills/Tech-stack
AWS | Attention Mechanisms | Azure | Distributed Computing | Domain Adaptation | Embeddings | Entity recognition | Fine Tuning | Google Cloud | Hugging Face | Hugging Face Transformers | Hyperparameter Tuning | Keras | LSTM | Langchain | Language Models | Large Language Models | MLOps | Model Compression | NLTK | Named Entity Recognition | Neural Networks | NumPy | OpenAI GPT | Pandas | Prompt engineering | PySpark | PyTorch | Python | Retrieval-Augmented Generation | SciPy | Scikit-learn | Semantic Search | Sentiment Analysis | Sequence Modeling | Spacy | TensorFlow | Text Classification | Tokenization | Transfer Learning | Transformers | Vector Databases
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