Senior AI/ML Engineer

A Little About Us

UniCourt is a leader in making court data more accessible and useful with our Legal Data as a Service (LDaaS). We provide real-time access to court data through our APIs and online app for business development and intelligence, litigation analytics, litigation tracking, case research, investigations, background checks, due diligence, compliance, underwriting, machine learning models, and process automation.

We provide access to court data from state and federal courts to a diverse list of clients, including Fortune 500 companies and AmLaw firms and industries such as legal, insurance, finance, investigations, government, education, nonprofits, and consumers.

UniCourt is a legal technology company focused on using technology to unlock the potential of legal data. We are based in both California and Mangalore, India and our team includes legal professionals, data scientists, physicists, computer engineers, and sales and marketing, professionals.

About the Job

We are seeking a passionate and driven Senior AI/ML Engineer with 3-4 years of hands-on experience to join our dynamic team. You will play a crucial role in developing and deploying cutting-edge machine learning solutions, mentoring junior engineers, and staying at the forefront of AI advancements. If you are a problem-solver with a strong foundation in machine learning, MLOps, and a keen interest in Large Language Models (LLMs), we want to hear from you!

Our company creates some of the world’s most cutting-edge software solutions in the legal industry. We solve difficult problems, work on innovative technology, and build world-class platforms for people and enterprises to interact with court records and other public data sets. With some of the best minds in the industry, we’re one of the most sought-after learning and career destinations in the world of legal tech. If you’re looking to work at a company with opportunities to forge your career path in technology, UniCourt is the right place for you.

Duties & Responsibilities

• Model Development and Training:
• Design, develop, and train machine learning models using various algorithms and techniques (e.g., regression, classification, clustering, deep learning).
• Conduct thorough data analysis, feature engineering, and model evaluation to ensure optimal performance.
• Experiment with different model architectures and hyperparameter tuning to achieve desired outcomes.
• MLOps and Model Deployment:
• Implement end-to-end MLOps pipelines for seamless model deployment, monitoring, and maintenance.
• Develop and maintain infrastructure for model serving, including containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
• Automate model retraining and deployment processes to ensure continuous improvement.
• Mentorship and Collaboration:
• Mentor and guide junior AI/ML engineers, fostering their technical growth and development.
• Collaborate effectively with cross-functional teams, including data scientists, software engineers, and product managers.
• Share knowledge and best practices within the team and contribute to a culture of continuous learning.
• Technology Exploration and Innovation:
• Stay up-to-date with the latest advancements in AI/ML, including emerging technologies and research papers.
• Proactively research and evaluate new tools, frameworks, and techniques to improve existing workflows and solutions.
• Identify opportunities to leverage LLMs for solving complex business problems.
• LLM Application:
• Apply knowledge of LLM's to practical problems.
• Experiment with different LLM's and prompt engineering to provide optimal results.
• Understand the limitations and capabilities of current LLM's.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.

Required Skills

• 3-4 years of hands-on experience in building and deploying machine learning models.
• Strong proficiency in programming languages such as Python.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid understanding of MLOps principles and tools.
• Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
• Experience mentoring others.
• Knowledge of Large Language Models (LLMs) and their applications.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.
• A strong desire to learn and adapt to new technologies.