Software Engineer

• Design and develop end-to-end products to enable easy adoption of generative AI for enterprises.
• Design and build services and integrations for ML pipelines for LLM fine-tuning, prompt tuning and engineering, Benchmarking and RAG for various generative AI models.
• Stay up to date with the latest advancements in the field of AI and apply them to develop cutting- edge solutions.
• Collaborate with multi-functional teams including product managers, applied scientists, and other engineers and identify and implement the most effective system design and solutions

Qualifications:

• Large Language Models (LLM):
  • Understanding and application, including fine-tuning
• Agentic frameworks:
  • Langchain, Langgraph, ReAct
• Chatbots and Conversational AI:
  • Design and implementation using platforms like Dialogflow
• Machine Learning Algorithms:
  • Supervised and unsupervised learning, reinforcement learning
• Deep Learning Frameworks:
  • TensorFlow, PyTorch, Keras
• Natural Language Processing (NLP):
  • NLTK, spaCy, Hugging Face Transformers
• Data Preprocessing and Feature Engineering:
  • Data cleaning, transformation, feature selection
• Data Pipelines:
  • Building and maintaining data workflows using tools like Apache Airflow, Luigi, MLFlow
• Deployment and Scaling:
  • Using platforms like AWS SageMaker, Google AI Platform, Azure ML, K8s, Docker
• Data Visualization:
  • Libraries like Matplotlib, Seaborn, Plotly
• Time Series Analysis:
  • Forecasting, anomaly detection, and trend analysis
• Anomaly Detection:
  • Techniques like Isolation Forest, One-Class SVM, Autoencoders