Company Overview:
Scientific research contains the most valuable knowledge humans have ever created. Yet, there’s no easy way to search and consume it.
This is the problem the Consensus team is obsessed with solving. Our mission is to democratize access to the world’s best knowledge.
Today, Consensus is an AI-powered academic search engine. We use the power of large language models to find, analyze, and synthesize insights in scientific research papers. We serve scientific researchers, students (high schoolers to PhDs), doctors & clinicians, industry R&D teams and the science-curious.
Try a search in Consensus for yourself: https://consensus.app/
Company Highlights:
- Since launching in the Winter of 2022, we’ve grown to over 400,000 monthly active users, 6M monthly searches and >$1M in recurring revenue.
- We are venture-backed with $15M in total funding from notable firms like Union Square Ventures, Nat Friedman, Daniel Gross and Draper Associates
- Our small but mighty team of 12 (and growing) includes alumni of top-tier tech companies, including Amazon, Google, Quora, PayPal, Waymo, and more.
- Consensus has been featured in The Wall Street Journal, The Atlantic, The New York Times, The Boston Globe, Nature, a16z, and is recognized as one of the most exciting applications of AI-powered search.
The Role:
We are looking for a Machine Learning Engineer to join our rockstar team. You’re a good candidate if you have experience in and enjoy building, fine-tuning, and deploying LLMs to enhance product capabilities and deliver impactful AI-driven solutions. Our AI features enhance search performance, generate answers from research papers, create informative study metadata, and synthesize findings across studies, enabling millions of users to conduct more efficient and informed research.
Experience we are looking for:
- Ability to own ML projects end-to-end, including definition, data gathering and labeling, model fine-tuning, and serving of final model
- Experience with big data platforms and distributed computing for efficient processing of data
- Working knowledge of GPUs for model training and inference, and understanding of distributed training and inference
- Enthusiasm for staying up to date on LLM research, and the ability to quickly implement novel techniques from cutting edge research papers
- Familiarity with model compression techniques such as quantization and distillation to improve efficiency and performance of LLMs
- Expertise in Python, and LLM-related packages such as transformers, pytorch/tensorflow, bitsandbytes, deepspeed, optimum
- Experience with serving in-product AI features
- Previous experience working in a fast-paced, early stage company environment
You are good fit at Consensus if you:
- Love science, research and truly believe in the power of knowledge
- Take pride in deep, high-quality work
- Get excited about creating something beautifully simple
- Are comfortable working hard and in fast-paced environments
- Are comfortable with lots of autonomy and minimal hand-holding
Compensation:
Salary: $150k - $225k USD
Competitive grant of fully diluted company equity
Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.