About Roots:
At Roots, our mission is to make work more human. We are developing fully autonomous, AI-powered Digital Coworkers that streamline tedious and repetitive tasks. By tackling core challenges in natural language understanding and computer vision, we are building an automation product that embodies the future of work. Our platform makes automation accessible to everyone, enabling users to generate automations by describing tasks in simple English, while solving complex business problems with enterprise-grade results and performance.
Our primary industry focus is Insurance, where success hinges on our customer’s ability to read and understand various unstructured legal, medical, and financial documents. Addressing this need, we've developed InsurGPT —a universal document understanding system that utilizes large language models specifically fine-tuned for the insurance industry, enhanced with Retrieval-Augmented Generation (RAG) technology and a touch of prompt engineering.
About the team:
Our team specializes in fine-tuning state-of-the-art custom models to meet specific business needs, surpassing GPT-4 in accuracy and efficiency. In addition to harnessing the power of pre-trained models, we are committed to building and refining our own multimodal models, tailored to the unique requirements of our use-cases. We take pride in developing custom inference endpoints that seamlessly integrate these models into our customers' workflows, providing low-latency, real-time document processing.
At Roots, we are committed to building a team of talented individuals who share our love for innovation and problem-solving. As we continue to expand, we are seeking a motivated AI Engineer to join our growing team.
Responsibilities:
- Develop machine learning systems to solve complex business problems and enhance the capabilities of InsurGPT.
- Collaborate with software engineers and DevOps team members to deploy models into production environments and integrate them with existing systems.
- Stay updated on the latest advancements in machine learning research and explore innovative approaches to drive continuous improvement.
- Work closely with cross-functional teams to understand requirements, prioritize tasks, and deliver solutions aligned with business objectives.
- Design and maintain systems to support strong SLAs on latency and uptime, while managing tradeoffs on resource consumption (CPU, GPU, memory, network)
- Improve our current MLOps infrastructure to streamline the deployment, monitoring, and oversight of our machine learning models.
- Improve vLLM/Triton inference endpoints for real-time integration of Large Language Models into product ecosystems.
- Monitor model performance in production environments and optimize system efficiency.
- Collaborate with teams and stakeholders, ensuring effective communication and presence in the office at least three days a week
Qualifications
- Graduate degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field.
- Proven experience as a Machine Learning Engineer or similar role, with a strong track record of developing and deploying machine learning models in production environments.
- Proficiency in Python and familiarity with machine learning libraries and frameworks such as PyTorch, Scikit-learn, Pandas, Numpy etc.
- Excellent knowledge and good practical skills in major ML algorithms as applied to large language models, traditional NLP, computer vision and information retrieval.
- Strong problem-solving skills, analytical thinking, and attention to detail, with the ability to translate business requirements into technical solutions effectively.
- Excellent written and verbal communication skills, with a strong emphasis on the written word. We highly appreciate public articles or blogs that highlight communication skills.
- Demonstrated ability to work independently, prioritize tasks, and manage multiple projects simultaneously in a fast-paced and dynamic environment.
As a startup, Roots Automation offers a high-paced environment with ample growth and learning opportunities across multiple disciplines. Equity ownership opportunities are available for the right candidate.
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