ML Engineer for OCR & NLP, Litigation Technology

Opportunity Overview:
We are working with a rapidly growing tech startup focused on innovative AI-driven solutions, and they're looking for a mid-level Machine Learning Engineer with expertise in OCR (Optical Character Recognition) and Natural Language Processing (NLP). This is a remote role, giving you the flexibility to work from anywhere in the U.S. You will have the opportunity to develop, deploy, and optimize machine learning models that power solutions used in litigation, such as automated document processing and intelligent data extraction from legal documents.

Why This Opportunity is Right for You:
This is a great opportunity for an ML Engineer who is passionate about building and deploying AI models in a fast-paced, innovative environment. The startup is growing quickly, and you will have the chance to play a key role in shaping their AI and ML offerings. You'll collaborate with a talented team, contribute to cutting-edge solutions, and gain experience in deploying models into production at scale.

Required Skills & Experience:

• Solid experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Expertise in OCR (Optical Character Recognition) and/or NLP (e.g., text classification, named entity recognition, sentiment analysis).
• Experience in developing and deploying machine learning models into production environments.
• Strong programming skills in Python (preferred) or another language.
• Experience with data preprocessing and working with large datasets.

Desired Skills & Experience:

• Familiarity with model optimization techniques (e.g., hyperparameter tuning, model pruning).
• Experience with containerization tools (Docker, Kubernetes).
• Familiarity with model monitoring, performance tracking in production, and prompt engineering.

What You Will Be Doing:

• Designing, developing, and deploying OCR and NLP models to automate document processing and data extraction used in litigation.
• Collaborating with product and engineering teams to integrate machine learning models into production systems.
• Optimizing models for better accuracy, efficiency, and scalability.
• Conducting experiments and fine-tuning models based on real-world feedback and data.
• Troubleshooting and iterating on deployed models to improve performance over time.

Tech Breakdown:

• 60% Model Development
• 30% Model Deployment and Optimization
• 10% Research and General Engineering

The Offer:

• Competitive salary
• Stock Options

You will receive the following benefits:

• Medical, Dental, and Vision Insurance.
• Generous Paid Time Off (PTO) and holidays.

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.