Multimodal Large Language Models AI Engineer

Multimodal Large Language Models AI Engineer

Job Description

San Francisco based AI for meetings startup is looking for experienced backend engineers. We’re developing a next generation real-time video communications platform, working at the cutting edge of real-time communications and human centered artificial intelligence. If you’re interested in making a large impact and are comfortable working in a fast paced, self-supervised environment, come join us!

As a senior AI Engineer, you will be working in a fast-paced environment which needs a mindset of a startup and an entrepreneur that is not hesitant to constantly shift gears, test and learn.

Key Qualifications

• MS or Ph.D in Computer Science, Electrical Engineering or related field with focus on machine learning, computer vision, speech processing, natural language understanding, human machine interaction, or similar.
• 3+ years of work experience in designing and developing enterprise-scale Large Language Model solutions in one or more of: Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Dialog Systems, Sentiment Analysis.
• 3+ years of work experience with transformer based language models
• Knowledge of GPT-X, HuggingFace Transformers
• Experience with fine-tuning and model optimizations (for inference speed / cost)
• Experience with Vision Based Transformers
• Knowledge of MLOps stacks such as GCP, Docker, REST APIs, scaling
• Experience in setting up supervised & unsupervised learning cloud NLP models including data cleaning, data analytics, feature creation, model selection & ensemble methods, performance metrics & visualization, and distillation.
• Fluency in programming languages including but not limited to Python.
• Proficiency in PyTorch and TensorFlow.
• Consistent track record of researching/inventing and shipping advanced machine learning algorithms based on NLP.
• Outstanding communication and interpersonal skills with ability to work well in cross functional teams.
• Published research on signal processing NLP, NLU or multimodal AI is a plus.
• Being a committer or a contributor to an open source project is a plus.

Responsibilities

• Research, design and implementation of machine learning/deep learning algorithms to support a real-time NLP data analytics platform for summarization, sentiment analysis, and topic discovery.
• Benchmarking and fine tuning of machine learning/deep learning algorithms
• Optimizing algorithms for real time in the cloud.
• Support algorithm integration into Headroom product.
• Stay up to date with tech, prototype with and learn new technologies, proactive in technology communities.
• Deliver on time with a high bar on quality of research, innovation and engineering.
• Develop & maintain NLP Pipeline for Document Data Extraction semantics and sentiment processing and understanding.
• Create products that provide a great user experience along with high performance, security, quality, and stability.

Team

Andrew Rabinovich - Co-Founder & CEO

Jon Pappas - Head of Product

Chloe Robertson

Karim Rahemtulla - Customer Success

Luis Orlando Carrión Ortiz - Director of Engineering

Warren Van Winckel - Director of Engineering

Josh Runge - Frontend Software Engineer

Pedro Garzon - Senior Machine Learning Engineer

Ivy Chang - Lead UX/UI Designer

Zachary Gilbert - Senior Software Engineer

Sound interesting? Apply! The Headroom team would love to hear from you.