Machine Learning Engineer
Core
Building production-grade ML models and pipelines for industrial contextualization, transforming unstructured data (manuals, P&IDs) into actionable intelligence using Deep Learning and Generative AI.
Role type
Senior Machine Learning Engineer (Production/Infrastructure)
Builds
Real-time industrial AI platform, data pipelines, and ML APIs
Domain
Industrial digitalization, Computer Vision, NLP, Generative AI
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, Hugging Face, LangChain, SQL, PySpark, Docker, Linux, MLOps, Cloud services (AWS/Azure/GCP)
Preferred skills
Vision-Language Models (VLMs), Computer Vision, RAG pipelines, Vector Databases (Pinecone/Milvus/Qdrant), Agentic frameworks (LangGraph), Columnar data (Parquet/Delta Lake/Iceberg), OCR
Technologies
PyTorch, TensorFlow, Hugging Face, LangChain, Docker, AWS, Azure, GCP, FastAPI, Flask, Pinecone, Milvus, Qdrant, LangGraph, Parquet, Delta Lake, Apache Iceberg
Responsibilities
Build and maintain robust data pipelines for large-scale industrial datasets; Deploy data science prototypes to production; Write high-quality, testable Python code for RESTful/gRPC APIs; Containerize applications and handle massive unstructured data volumes; Run experiments and fine-tune foundational models (NLP, Vision-Language); Write unit/integration tests and monitor deployed models for drift; Collaborate with senior engineers and product managers on technical roadmap.
Seniority
Mid-Senior, hands-on IC
