Harnham
Staff Machine Learning Engineer - NLP & LLMs
Harnham - New York, New York, us, 10261
Work at Harnham
Overview
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Overview
Staff Machine Learning Engineer - NLP & LLMs
Location:
Fully Remote Compensation:
$250,000 - $275,000 base salary + bonus + benefits
ABOUT THE COMPANY
We are partnered with a market leader in the legal and financial services industry, driving innovation through AI. This company is revolutionizing how professionals interact with data by integrating cutting-edge NLP and LLM technologies. As their platform scales, they are seeking a highly skilled
Machine Learning Engineer
to take the lead in developing, deploying, and optimizing advanced AI models that directly impact high-value, high-regulation environments.
This is an opportunity to build mission-critical systems from the ground up and work alongside some of the top minds in AI and law.
THE ROLE
As a
Staff
Machine Learning Engineer , you will work closely with researchers and the C-suite to design and implement robust machine learning infrastructure and end-to-end NLP/LLM pipelines. You will bridge the gap between experimentation and scalable deployment, contributing to the full lifecycle of AI products.
Your Responsibilities Will Include: Model Deployment & Scaling:
Engineer and deploy large-scale NLP and LLM models for production environments. Infrastructure & Tooling:
Build and maintain data pipelines, training workflows, and inference systems optimized for low-latency and high-accuracy. End-to-End Development:
Take PoCs from research stage to production-grade systems, focusing on performance, reliability, and maintainability. Optimization:
Improve existing model architectures and fine-tune LLMs using retrieval-augmented generation (RAG), prompt tuning, quantization, and efficient inference techniques. Collaboration:
Partner with Applied Scientists, Legal SMEs, and Product Leaders to align technical solutions with business and user needs. Code Quality:
Write clean, scalable, and well-documented code using industry best practices. YOUR SKILLS AND EXPERIENCE
We are looking for an experienced and versatile
Staff
Machine Learning Engineer
with the following qualifications:
5+ years
of experience deploying NLP and ML models in production environments. Strong software engineering background in
Python , with experience using frameworks like
TensorFlow, PyTorch, spaCy, Hugging Face Transformers , and more. Demonstrated ability to scale models and build distributed training/inference systems. Experience working with large datasets and knowledge of data pipelines, MLOps tools (e.g., MLflow, Kubeflow, Airflow), and cloud infrastructure (AWS, GCP, or Azure). Deep understanding of NLP concepts and LLM architectures (BERT, GPT, T5, etc.). Comfortable working cross-functionally with researchers, product teams, and senior leadership. Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (PhD a plus, but not required). Bonus: Contributions to open-source NLP projects or publications in applied ML conferences (NeurIPS, ACL, EMNLP, etc.) BENEFITS
Top-Tier Compensation:
Base salary of $250,000 - $275,000 + annual bonus. Fully Remote:
Work from anywhere in the United States. Ownership:
End-to-end responsibility for the models and systems you help build. Health & Retirement:
Comprehensive medical, dental, vision, and 401(k) plans. Research-Driven Culture:
Collaborate with world-class researchers and engineers solving impactful real-world problems.
HOW TO APPLY
Interested applicants should submit their resume to
Tim Jonas
via the
Apply
link on this page. We look forward to seeing how your engineering skills can help shape the future of legal and financial AI systems.
KEYWORDS: Machine Learning | ML Engineering | NLP | LLMs | Deep Learning | Large Language Models | MLOps | Python | PyTorch | Hugging Face | TensorFlow | Cloud Infrastructure | Distributed Systems | RAG | Prompt Engineering | AI Platforms | Legal Tech | Financial Services | Applied ML | Model Deployment
Location:
Fully Remote Compensation:
$250,000 - $275,000 base salary + bonus + benefits
ABOUT THE COMPANY
We are partnered with a market leader in the legal and financial services industry, driving innovation through AI. This company is revolutionizing how professionals interact with data by integrating cutting-edge NLP and LLM technologies. As their platform scales, they are seeking a highly skilled
Machine Learning Engineer
to take the lead in developing, deploying, and optimizing advanced AI models that directly impact high-value, high-regulation environments.
This is an opportunity to build mission-critical systems from the ground up and work alongside some of the top minds in AI and law.
THE ROLE
As a
Staff
Machine Learning Engineer , you will work closely with researchers and the C-suite to design and implement robust machine learning infrastructure and end-to-end NLP/LLM pipelines. You will bridge the gap between experimentation and scalable deployment, contributing to the full lifecycle of AI products.
Your Responsibilities Will Include: Model Deployment & Scaling:
Engineer and deploy large-scale NLP and LLM models for production environments. Infrastructure & Tooling:
Build and maintain data pipelines, training workflows, and inference systems optimized for low-latency and high-accuracy. End-to-End Development:
Take PoCs from research stage to production-grade systems, focusing on performance, reliability, and maintainability. Optimization:
Improve existing model architectures and fine-tune LLMs using retrieval-augmented generation (RAG), prompt tuning, quantization, and efficient inference techniques. Collaboration:
Partner with Applied Scientists, Legal SMEs, and Product Leaders to align technical solutions with business and user needs. Code Quality:
Write clean, scalable, and well-documented code using industry best practices. YOUR SKILLS AND EXPERIENCE
We are looking for an experienced and versatile
Staff
Machine Learning Engineer
with the following qualifications:
5+ years
of experience deploying NLP and ML models in production environments. Strong software engineering background in
Python , with experience using frameworks like
TensorFlow, PyTorch, spaCy, Hugging Face Transformers , and more. Demonstrated ability to scale models and build distributed training/inference systems. Experience working with large datasets and knowledge of data pipelines, MLOps tools (e.g., MLflow, Kubeflow, Airflow), and cloud infrastructure (AWS, GCP, or Azure). Deep understanding of NLP concepts and LLM architectures (BERT, GPT, T5, etc.). Comfortable working cross-functionally with researchers, product teams, and senior leadership. Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field (PhD a plus, but not required). Bonus: Contributions to open-source NLP projects or publications in applied ML conferences (NeurIPS, ACL, EMNLP, etc.) BENEFITS
Top-Tier Compensation:
Base salary of $250,000 - $275,000 + annual bonus. Fully Remote:
Work from anywhere in the United States. Ownership:
End-to-end responsibility for the models and systems you help build. Health & Retirement:
Comprehensive medical, dental, vision, and 401(k) plans. Research-Driven Culture:
Collaborate with world-class researchers and engineers solving impactful real-world problems.
HOW TO APPLY
Interested applicants should submit their resume to
Tim Jonas
via the
Apply
link on this page. We look forward to seeing how your engineering skills can help shape the future of legal and financial AI systems.
KEYWORDS: Machine Learning | ML Engineering | NLP | LLMs | Deep Learning | Large Language Models | MLOps | Python | PyTorch | Hugging Face | TensorFlow | Cloud Infrastructure | Distributed Systems | RAG | Prompt Engineering | AI Platforms | Legal Tech | Financial Services | Applied ML | Model Deployment