ML Engineers - with LLM GenAI

Job Title: ML Engineers - with LLM GenAI (3 Resources)

• Write efficient machine learning workflows and pipelines
  • Training pipeline - Ingest/Preprocess/Vectorize and index data
  • Inference pipeline - AI Guided workflow to respond to user requests or provide proactive recommendations
• Measure Model metrics to evaluate the performance of the model (Predictive & Gen AI metrics) - ( F1 Score, Faithfulness, Answer Relevancy etc. )
• Evaluate and compare model performance for specific tasks to enable picking the optimal models
• Apply Guardrails for both inputs and outputs
• Identify areas of improvements for machine learning pipelines and models and implement them
• Collaborate with Data scientists, MLOps/Devsecops and UX engineers to implement the solution
• Collaborate with cross functional teams to translate business requirements into ML solutions
• Document and communicate, ml workflows, algorithms and solutions to technical and non-technical stakeholders
• AI application experience with Network Domain solutions would be a plus

• ML Engineer with 4-6 Years of relevant experience
• Excellent experience with Python NLP libraries (NLTK, gensim, spacy etc.)
• Good experience with deploying production models for Classification / Regression tasks
• Working experience with LLM Application frameworks like langchain
• Working experience with LLM Data and pre-processing frameworks like Llamaindex and unstructured.io Unstructured | The Unstructured Data ETL for Your LLM
  Unstructured helps you get your data ready for AI by transforming it into a format that large language models can understand. Easily connect your data to LLMs.
  unstructured.io
• Experience with applying guardrails for machine learning workflows. Experience with nemo-guardrails for LLM and microsoft presidio or any other PII removal frameworks
• Working experience with open source and commercial LLM models
• Working experience in benchmarking embedding models (both open and closed source) for vectorization and indexing
• Working experience on integrating with any Vector Databases (elastic, quadrant etc.)
• Experience with any MLOps frameworks (open source or commercial) would be a plus
• Experience with any cloud based AI platforms (Sagemaker, Vertex AI etc.)
• Experience with HungginFace libraries (SentenceTransformers etc.)
• Adept at prompt engineering - Using the right prompts that maximises the accuracy of the Models response
• Excellent experience with Python and the related ecosystem for package management
• Rust, Go or C for compute efficient workflows like efficient model serving would be a plus
• Excellent knowledge of Notebook environment (Jupyter, VS Code IDE) for experimentation and development
• Good experience with Git platforms and development workflows (Github, Gitlab etc.)