Machine Learning Engineer
Core
End-to-end Machine Learning and LLM engineering across diverse domains including fish, trains, clothes, money, pets, and office spaces.
Role type
Senior Machine Learning Engineer (LLM & MLOps)
Builds
Production ML and LLM models, data pipelines, and APIs for external clients and internal startup projects.
Domain
Machine Learning, Large Language Models (LLM), MLOps, and LLMOps across varied industries.
Deliverable
production ML models
Required skills
Python, software engineering best practices, ML and deep learning algorithms, LLM frameworks, model deployment, data pipeline construction, API development, model monitoring and optimization
Preferred skills
R, transformer-based architectures, LLM fine-tuning, prompt engineering, RAG, vector databases, DevOps, Kubernetes, serverless architectures
Technologies
Python, R, Scikit-learn, LangChain, LlamaIndex, LangGraph, CrewAI, AWS, GCP, Azure, DVC, Github Actions, Sagemaker, VertexAI, AzureML, Airflow, AWS Step functions, Docker, Kubernetes, Terraform, Pinecode, redis, ElasticSearch
Responsibilities
Analyze and plan problems and solutions with stakeholders; preprocess data and create datasets; develop, fine-tune, and evaluate ML/LLM models; validate results and ensure model interpretability; build and optimize data pipelines and infrastructure; develop APIs and integrate models into production; ensure scalability and performance of deployed models
