Machine Learning Engineer – NLP / Production ML

Machine Learning Engineer – NLP / Production ML A fantastic opportunity for a Machine Learning Engineer to join a growing AI technology company transforming complex enterprise data into high-quality datasets for AI development. You will take ownership of production NLP models and data pipelines, improving how sensitive information is identified and de-identified while preserving the usefulness of the data.

This role requires hands-on production ML experience, strong Python engineering and a track record of improving models through retraining, error analysis and measurable results.

Location

Brooklyn, New York, NY. In-office, five days per week. Relocation bonus of up to $10,000 available.

Salary: $180,000–$330,000 annual base salary + competitive equity Requirements for Machine Learning Engineer: 3+ years of professional experience in machine learning or software engineering, with hands-on responsibility for deploying and improving production ML models Strong Python software engineering skills, including working within production systems and data pipelines Applied NLP experience, particularly named entity recognition, entity resolution, document processing or de-identification Experience retraining models, investigating failures to generalize, and developing datasets and labels to address those failures Clear evidence of shipping measurable improvements in both model precision and recall Experience working at at least one startup, alongside a strong engineering track record and clear career progression Hands-on AWS experience Strong problem-solving skills and the ability to select practical approaches based on evaluation results Able to work from the Brooklyn office five days per week Bachelor’s degree in a STEM discipline from a highly ranked, leading US or international university, with a history of excellent academic achievement Experience with PyTorch, transformer fine-tuning, GLiNER, active learning, LLM-assisted labeling, inference optimization or multimodal models is beneficial Responsibilities for Machine Learning Engineer: Own and improve production models that identify and de-identify sensitive enterprise information Retrain models, analyze errors and deliver measurable improvements in precision and recall Develop scalable labeling strategies using active learning and LLM-assisted review Combine deterministic rules, classical machine learning, fine-tuned models and LLM-based approaches to solve NLP problems Build evaluation benchmarks and experiment infrastructure to make model improvements reliable and repeatable Extend data processing capabilities into new formats, including audio, video and tabular data Work within Python-based production pipelines on AWS Collaborate with the engineering team to turn model improvements into reliable production functionality What this role offers: Ownership of production NLP models and data pipelines supporting the development of advanced AI systems Technically challenging work across sensitive data processing, model evaluation and new data modalities A competitive base salary, equity opportunity and direct impact within a small, growing engineering team Applications: If you would like to apply for this unique Machine Learning Engineering role, please submit your resume through the relevant application link!

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Keywords

Machine Learning Engineer / Applied Machine Learning Engineer / NLP Engineer / AI Engineer / Applied AI Engineer / ML Software Engineer / Production ML Engineer / Python Software Engineer / NLP Software Engineer / ML Systems Engineer / Deep Learning Engineer / Applied Scientist / Python / PyTorch / Transformers / Named Entity Recognition / Entity Resolution / GLiNER / ONNX Runtime / TensorRT / AWS / Embeddings / Active Learning / Large Language Models / Document Processing / Data Pipelines / Model Evaluation / Multimodal Models / Data De-identification / Computer Science / Mathematics / Statistics / Engineering / Physics RedTech Recruitment Ltd focuses on finding roles for Engineers and Scientists.

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