Job summary
Job post source
This job is directly from Baselayer
Job overview
The Machine Learning Engineer role at Baselayer involves developing and optimizing ML models to enhance fraud prevention and compliance for financial institutions, contributing to cutting-edge AI solutions in a high-impact fintech environment.
Responsibilities and impact
The engineer will build and maintain scalable ML models, design ML systems for KYC/KYB processes, develop data pipelines, implement advanced ML techniques like RLHF and LoRA, ensure model governance and compliance, optimize performance, and conduct experiments to improve model architectures.
Compensation and benefits
The position offers a salary range of $150k to $225k plus equity (0.05% to 0.25%), hybrid work in San Francisco with 3 days in office per week, flexible PTO, healthcare, and 401K benefits.
Experience and skills
Candidates should have 1-3 years of machine learning development experience with Python, strong AI/ML fundamentals especially with LLMs, experience handling large-scale data, and a focus on responsible AI practices in regulated environments like KYC/KYB.
Career development
The role offers opportunities to work with cutting-edge AI technologies and learn from experienced founders and experts, fostering growth in advanced ML techniques and fintech applications.
Work environment and culture
Baselayer promotes a high-trust, ownership-focused environment with a smart, genuine, and ambitious team, emphasizing radical candor and feedback for continuous improvement.
Company information
Baselayer is a fintech startup founded in 2023, specializing in fraud prevention and compliance for financial institutions, with $20 million raised and over 2,000 customers including financial institutions and government agencies.
Job location and travel
The job is hybrid based in San Francisco, requiring in-office presence three days a week.
Unique job features
The role involves working on innovative AI solutions for identity verification using advanced ML techniques like reinforcement learning from human feedback and parameter-efficient fine-tuning methods.
Company overview
Baselayer is a technology company specializing in the design and manufacture of modular data center infrastructure, providing solutions that enable rapid deployment, scalability, and efficient energy use for enterprise and cloud computing clients. The company generates revenue by selling its modular data center products, offering related services such as installation, maintenance, and monitoring, and partnering with organizations seeking flexible, high-performance IT environments. Founded in 2014 as a spin-off from IO Data Centers, Baselayer has played a significant role in advancing the adoption of modular, portable data center technology across industries. Its innovations focus on sustainability, operational efficiency, and adaptability to evolving digital demands. Candidates should be aware of Baselayer's emphasis on engineering excellence and its reputation for delivering robust, future-ready infrastructure solutions.
How to land this job
Tailor your resume to highlight your experience with Python and machine learning model development, emphasizing your ability to handle large-scale data and optimize computational performance, as these are key for Baselayer's ML Engineer role.
Focus on showcasing your knowledge of AI/ML fundamentals, particularly your work with large language models (LLMs), reinforcement learning, and fine-tuning techniques like LoRA, aligning with Baselayer's cutting-edge AI solutions.
Apply through multiple channels including Baselayer's corporate website, LinkedIn, and relevant job boards to maximize your application's visibility and reach.
Connect with current Baselayer employees in the machine learning or AI divisions on LinkedIn; start conversations by referencing Baselayer’s rapid growth, recent press releases, or asking about their experience working on KYC/KYB ML systems to break the ice.
Optimize your resume for ATS by incorporating keywords such as 'machine learning,' 'Python,' 'LLMs,' 'reinforcement learning,' 'model governance,' and 'KYC/KYB compliance' to ensure your resume passes automated screenings.
Utilize Jennie Johnson's Power Apply feature to automate tailored applications, identify multiple application portals, and discover LinkedIn contacts to network with, allowing you to focus on preparing for interviews and skill development.
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