Senior Machine Learning Engineer

Harnham; United States; Remote; USD 180,000 - 210,000; Full time

Job summary

Harnham is seeking a Mid-Level Machine Learning Engineer to join a financial services firm focused on AI technologies. This role involves developing and optimizing NLP models within a collaborative environment, ideal for someone with a solid foundation in machine learning and a passion for growth. The position offers a competitive salary range of $180,000 - $210,000, flexible remote work, and opportunities for professional development.

Benefits

Competitive Compensation: $180,000 – $210,000 base + bonus.

Flexible & Remote: Work from anywhere in the United States or Canada.

Comprehensive medical, dental, and vision benefits.

401(k) plan.

Opportunities for professional growth.

Qualifications

• 3–5 years of experience building and deploying ML models, especially in NLP.
• Proficient in Python and familiar with ML libraries.
• Degree in Computer Science or related field.

Responsibilities

• Develop and optimize NLP models and AI infrastructure.
• Collaborate with teams to deliver ML-powered features.
• Manage data pipelines and support model evaluation.

Skills

Python

NLP

Machine Learning

Education

Bachelor’s degree in Computer Science

Tools

TensorFlow

PyTorch

spaCy

Hugging Face Transformers

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

$180,000.00/yr - $210,000.00/yr

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Remote - United States

$180,000 - $210,000

ABOUT THE COMPANY

We’re working with a cutting-edge financial services company transforming the legal space through advanced AI. Their mission: to make legal and financial workflows smarter, faster, and more cost-effective by leveraging the latest in natural language processing and machine learning. As they continue to expand their AI capabilities, they’re seeking a Machine Learning Engineer (Mid-Level) to join their growing NLP/LLM team.

This is a great opportunity for someone with solid production-level ML experience who wants to take the next step—working closely with seasoned researchers, engineers, and product leaders to build next-generation AI systems in a high-impact domain.

THE ROLE

As a Machine Learning Engineer, you’ll contribute to the development, deployment, and optimization of NLP models and AI infrastructure. You’ll be responsible for translating cutting-edge research into scalable, production-ready systems and collaborating with teams across engineering, research, and product.

Key Responsibilities:

• Model Development & Integration: Work with senior engineers and researchers to develop and integrate LLMs and NLP models into customer-facing products.
• Production-Ready Code: Build and maintain model pipelines that are scalable, testable, and efficient.
• Data Engineering: Help design and manage data pipelines, labeling workflows, and model training datasets.
• Model Tuning & Evaluation: Assist in prompt engineering, fine-tuning, evaluation, and benchmarking of NLP models.
• Collaboration: Partner with applied scientists and product teams to deliver end-to-end features powered by machine learning.
• Learning & Growth: Expand your skills through mentorship and exposure to cutting-edge NLP/LLM work and tooling.

YOUR SKILLS AND EXPERIENCE

We’re looking for a motivated engineer with a strong foundation in machine learning and an eagerness to grow within a fast-moving team.

Required Qualifications:

• 3–5 years of professional experience building and deploying ML models (with at least 2 years focused on NLP).
• Proficient in Python and familiar with ML libraries like TensorFlow, PyTorch, spaCy, or Hugging Face Transformers.
• Experience with model training, evaluation, and deployment in cloud environments (e.g., AWS, GCP, or Azure).
• Comfortable working with large datasets, data preprocessing, and version control tools (e.g., Git, DVC).
• Knowledge of modern NLP concepts and language model architectures (e.g., BERT, GPT, T5).
• Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s a plus).

Bonus Points For:

• Experience with MLOps tools (e.g., MLflow, Airflow, Kubernetes).
• Previous work with legal, financial, or highly regulated data.
• Contributions to open-source NLP tools or public research.

BENEFITS

• Competitive Compensation: $180,000 – $210,000 base + bonus.
• Flexible & Remote: Work from anywhere in the United States or Canada.
• Health & Wellness: Comprehensive medical, dental, vision, and 401(k).
• Professional Growth: Work alongside experienced engineers and researchers in a high-learning environment.
• Impact: Contribute to real-world AI products used by professionals in law and finance.

HOW TO APPLY

Send your resume to Grace McCarthy via the Apply link on this page. We’re excited to meet engineers who want to build meaningful, AI-driven systems in a space that matters.

KEYWORDS:

Machine Learning | NLP | LLM | Deep Learning | Generative AI | Model Deployment | Python | PyTorch | TensorFlow | Hugging Face | Prompt Engineering | ML Pipelines | Legal Tech | Financial Services | AI Infrastructure | Mid-Level Engineer | Scalable AI Systems

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Engineering, and Product Management

• Industries

  Engineering Services, Research Services, and Technology, Information and Media

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