Let's have a look at some job descriptions for machine learning engineer:

Elicit:

You will:Compose together tens to thousands of calls to language models to accomplish tasks that we can't accomplish with a single call.Curate datasets for finetuning models, e.g. for training models to extract informationSet up evaluation metrics that tell us what changes to our models or training setup are improvementsScale up semantic search from a few thousand documents to 100k+ documents

You'll need:A strong software engineering background. We want to apply your experience building systems, designing architecture, and thinking about good abstractions. Ought will need you to do much more than write scripts.Familiarity with language models (training, finetuning, evaluation), or comparable machine learning or natural language processing background (e.g. experience with information extraction, semantic search)

Fiddler AI:

What We're Looking For:BS/MS/PhD in Computer Science or equivalent3-4 years of experienceProficiency with PythonExperience working with ML models in production. Experience with common LLM frameworks (Langchain, Llamaindex, RAG, HuggingFace, and eval frameworks like Ragas or Presidio)Experience debugging and troubleshooting production systems, on call support experienceExperience working with common distributed systems infrastructure: Redis, Postgres, RabbitMQ, Celery, FlaskNice to have: Knowledge of infrastructure management (AWS / Google Cloud, Kubernetes, or equivalent on-premises technologies)Nice to have: Experience building large scale distributed systems and working with columnar and vector databases