Staff Machine Learning Engineer

Harnham; United States; Remote; USD 250,000 - 275,000; Full time

Job summary

A leading company in the legal and financial sector is looking for a Staff Machine Learning Engineer to develop robust machine learning infrastructure and optimize AI models. This fully remote role requires expertise in NLP and ML, with a competitive salary and benefits package. Join a team focused on innovation and driving impactful solutions using advanced AI technologies.

Benefits

Comprehensive medical, dental, and vision plans

401(k) plans

Ownership of models and systems built

Collaborative research-driven culture

Qualifications

• 5+ years of experience deploying NLP and ML models in production environments.
• Strong software engineering background in Python.
• Experience with cloud infrastructure (AWS, GCP, Azure) required.

Responsibilities

• Engineer and deploy large-scale NLP and LLM models for production.
• Build and maintain data pipelines and training workflows.
• Collaborate cross-functionally with researchers and legal SMEs.

Skills

NLP

Machine Learning

Python

Distributed Systems

Data Pipelines

Education

Bachelor's or Master's degree in Computer Science

Tools

TensorFlow

PyTorch

Hugging Face

MLflow

Job description

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This range is provided by Harnham. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$250,000.00/yr - $275,000.00/yr

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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 Grace McCarthy 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

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Science

• Industries

  Legal Services, Financial Services, and Software Development

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