Machine Learning Engineer
Core
End-to-end Machine Learning and LLM engineering for diverse client projects involving data analysis, model development, and production deployment.
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 Data Engineering.
Deliverable
production ML models | product features | infrastructure
Required skills
Python, ML and deep learning algorithms, LLM frameworks, software engineering best practices, model deployment, data pipeline construction, API development, scalability optimization.
Preferred skills
Deep learning frameworks, transformer 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 ML problems with stakeholders; preprocess data and engineer features; 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, monitoring, and performance optimization.
Seniority
Senior, hands-on IC
