Senior Machine Learning Engineer - San Diego, United States - Amicus Therapeutics
Description
About AmicusAmicus is an AI startup dedicated to revolutionizing the professional services industry.
Our mission is to automate mundane and repetitive tasks in legal firms, consulting firms, and similar sectors, freeing up professionals to focus on higher-value activities.
Our innovative approach leverages the latest in AI technology to create solutions that are fundamentally transformative.
Do you thrive in a high velocity, collaborative environment, fueled by curiosity and a never-ending desire to break status-quo? If so, let's chat.
As an early member of our engineering team, you will play a pivotal role in shaping the direction of our product and technology.
We are seeking exceptional candidates who are driven by challenges, thrive on hard work, and have a deep technical expertise that can contribute to the high-velocity growth of our startup.
This role is perfect for someone who is gritty, self-directed, and passionate about creating impactful technological solutions in a fast-paced environment.
We are in search of a visionary Senior Machine Learning Engineer to spearhead the enhancement of our retrieval models, which are integral to our RAG process.
This role will focus on tailoring our retrieval systems to effectively select pertinent documents that serve as the knowledge foundation for subsequent generative tasks.
Exciting challenges:
Be part of the team that pushes the boundaries of AI and creates the world's first AI lawyer. Partner with like-minded engineers from other companies to solve common problems (ex. RAG, fine-tuning approaches etc.)
Extract insights from large scale unstructured documents, while maintaining security and privacy for highly sensitive client data
Redefine human-computer interaction as we seek to build an AI agent
Help build our engineering team
What You'll Do:
Lead the development of top-tier retrieval models that are optimized for the retrieval-augmented generation (RAG) process, ensuring the delivery of highly relevant source material for generative models
Enhance our RAG framework to improve document encoding, scoring, and selection mechanisms, with an emphasis on natural language understanding
Undertake rigorous experimentation and analysis to benchmark retrieval models against industry standards, focusing on both precision and adaptability for generative tasks
Collaborate with product teams to ensure seamless integration and alignment of retrieval and generative components
Drive innovation by staying abreast of emerging trends and methodologies in retrieval systems and their applications within RAG frameworks
Create pipelines to process and analyze documents on a large scale to provide insights for customers
What You'll Need:
5+ years of hands-on experience with retrieval models, including experience in a RAG or similar context utilizing retrieval to enhance generative processes
Demonstrated experience with modern retrieval techniques such as dense passage retrieval (DPR), contrastive learning, or other advanced retrieval methods
Familiarity with transformer models and sequence-to-sequence learning, particularly as it relates to document retrieval for generation
Strong analytical skills, with a proven track record of tackling complex problems involving large-scale, multimodal data
Experience with machine learning lifecycle management, from model development to production deployment
Previous experience in a startup environment or as a founding ML Engineer
Pay Transparency
Amicus strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team.
Our salary ranges are based on paying competitively for our size, stage and industry, and are one part of many compensation, benefits and other reward opportunities we provide.
There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team.
The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description.
In this case, we will communicate any updates in the expected salary range.Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates.
Salary range:
$175,000 - $225,000 USD
Benefits
Competitive salary
Significant equity as a founding employee
100% coverage for medical, dental, and vision plans for both employees and their families
Unlimited paid time off
Flexible working hours and the ability to work 100% remotely
Company computer and custom setup as needed
Compensation Range:
$140K - $180K
#J-18808-Ljbffr