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.

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

You must have personally trained or fine-tuned NLP extraction models, deployed them into production, and improved them through error analysis and retraining. Experience limited to LLM APIs, prompt engineering, RAG/search pipelines or ML infrastructure will not meet this role’s requirements.

Requirements for Machine Learning Engineer:

• 3 years of professional experience in machine learning or software engineering, excluding internships and academic research, with hands-on responsibility for deploying and improving production ML models
• Experience personally training or fine-tuning production NLP models for named entity recognition, entity resolution, sensitive-data detection or structured information extraction from documents
• Strong Python software engineering skills, including building and maintaining production systems, model inference services and data pipelines
• Experience analyzing false positives and false negatives, improving training datasets or labels, and retraining models to deliver measurable improvements against precision and recall requirements
• Experience investigating model failures on new or unfamiliar data and making targeted improvements to address them
• Hands-on engineering experience at at least one startup, shipping and maintaining a product used by customers or business users, alongside a strong engineering track record and clear career progression
• Hands-on experience deploying or operating production software or ML workloads on AWS
• Strong problem-solving skills and the ability to choose between rules, classical ML, fine-tuned models and LLM-based approaches using evaluation results
• Able to work from the Brooklyn office five days per week
• A strong academic background in a relevant STEM discipline is preferred, particularly a degree from a highly ranked university; relevant PhDs completed or nearing completion are also welcomed
• Direct de-identification experience is particularly valuable, alongside experience with PyTorch, transformer fine-tuning, GLiNER, active learning, LLM-assisted labeling, inference optimization or multimodal models

Responsibilities for Machine Learning Engineer:

• Own and improve production NLP models that identify and de-identify sensitive enterprise information
• Investigate model errors, develop better training datasets and labels, and retrain models to improve precision, recall and generalization
• 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 entity recognition and resolution 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
• Build and maintain 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 Machine Learning Engineering role, please submit your resume through the relevant application link. Please ensure your resume clearly describes the NLP models you personally trained or fine-tuned, your role in deploying and retraining them, and how you measured improvements.

We’re committed to creating an inclusive and accessible hiring process. If you require reasonable accommodations for your application or during the review process, please let us know by separately emailing applications@redtech-recruit.com (if this email address has been removed by the job board, full contact details are available on our website).

Keywords: Machine Learning Engineer / Applied Machine Learning Engineer / NLP Engineer / Production ML Engineer / ML Software Engineer / Python Software Engineer / NLP Software Engineer / Applied Scientist / Python / PyTorch / Transformers / Named Entity Recognition / Entity Resolution / Sensitive Data Detection / Structured Information Extraction / GLiNER / ONNX Runtime / TensorRT / AWS / Active Learning / Transformer Fine-Tuning / Data Pipelines / Model Evaluation / Precision / Recall / Model Retraining / Multimodal Models / Data De-identification / Computer Science / Mathematics / Statistics / Engineering / Physics

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