Senior NLP & ML Engineer — Remote, Scalable AI

Tekmetric; United States; On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Remote work

Health benefits

Paid time off (PTO)

Parental leave

401(k) match

FSA/HSA

Home office stipend

Job summary

Tekmetric is seeking a Machine Learning Engineer specializing in NLP and large-scale data processing. You will build NLP/ML models for document classification and OCR extraction from PDFs, powering an intelligent search system.

You will experiment with LLMs, embeddings, transformers, and vector databases, creating scalable pipelines and deploying models on AWS and Kubernetes. Collaboration with data engineers is essential.

Qualifications

• 5+ years of experience in Machine Learning and NLP.
• Strong Python skills and experience with ML/NLP frameworks.
• Familiarity with transformer architectures (BERT, GPT, T5).
• Experience with text classification and embeddings.
• Knowledge of OCR techniques (Tesseract, Textract, OpenCV).
• Hands-on experience with AWS, Kubernetes and Airflow.
• Strong understanding of information retrieval and search ranking.

Responsibilities

• Develop and train NLP/ML models for document classification and entity recognition.
• Experiment with LLMs, embeddings, transformers, and vector databases.
• Build pipelines combining rule-based methods with ML models for classification.
• Apply OCR to extract structured data from PDFs and scanned documents.
• Deploy ML models in production using Kubernetes and AWS services.
• Collaborate with data engineers to integrate models into search APIs and data pipelines.
• Utilize Spark/EMR for large-scale ML processing.

Skills

Machine Learning

NLP

Python

AWS

Kubernetes

Airflow

ElasticSearch/OpenSearch

Transformer models

Text classification

Tools

Hugging Face

spaCy

NLTK

TensorFlow

PyTorch

Tesseract

Textract

OpenCV

Job description

Tekmetric is seeking a Machine Learning Engineer specializing in NLP and large-scale data processing. You will build NLP/ML models for document classification and OCR extraction from PDFs, powering an intelligent search system.

You will experiment with LLMs, embeddings, transformers, and vector databases, creating scalable pipelines and deploying models on AWS and Kubernetes. Collaboration with data engineers is essential.