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Machine learning engineer Jobs in Berkeley, CA

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Machine learning engineer • berkeley ca

Last updated: 1 day ago
  • Promoted
Machine Learning Engineer

Machine Learning Engineer

BASELAYERSan Francisco, CA, United States
Full-time
Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk.Baselayer's B2B risk solut...Show moreLast updated: 1 day ago
Machine Learning Engineer Job at Middesk in San Francisco

Machine Learning Engineer Job at Middesk in San Francisco

MiddeskSan Francisco, CA, United States
Full-time
About Middesk Middesk makes it easier for businesses to work together.Since 2018, we’ve been transforming business identity verification, replacing slow, manual processes with seamless access to co...Show moreLast updated: 30+ days ago
  • Promoted
Founding Infrastructure Engineer

Founding Infrastructure Engineer

ReductoSan Francisco, CA, United States
Full-time
Reducto helps AI teams ingest real world enterprise data with state of the art accuracy.The vast majority of enterprise data from financial statements to health records is locked in unstructured fi...Show moreLast updated: 15 days ago
  • Promoted
Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)

Senior Machine Learning Engineer - Discovery (ML + Backend Engineering)

ScribdSan Francisco, CA, United States
Full-time
At Scribd (pronounced scribbed), our mission is to spark human curiosity.Join our team as we create a world of stories and knowledge, democratize the exchange of ideas and information, and empower ...Show moreLast updated: 1 day ago
  • Promoted
Machine Learning Engineer

Machine Learning Engineer

KreaSan Francisco, CA, United States
Full-time
At Krea, we are building next-generation AI creative tools.We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that empower human creativity, not re...Show moreLast updated: 1 day ago
  • Promoted
Machine Learning Engineer

Machine Learning Engineer

Two Dots IncSan Francisco, CA, United States
Full-time
Two Dots is using AI to remake the way consumer underwriting is done, starting with residential real estate.Most consumers' most important financial information is locked up in documents, and we've...Show moreLast updated: 1 day ago
Growth & Marketing Engineer

Growth & Marketing Engineer

RelaceSan Francisco, CA, United States
Full-time
Relace is building the models and infrastructure that code agents reach for.We power the fastest model on OpenRouter (10,000 tok) and deliver optimized small language models designed for retrieval,...Show moreLast updated: 30+ days ago
Machine Learning Engineer

Machine Learning Engineer

DeWinter GroupSan Francisco, CA
Full-time
Our client, a leader in Social Media and Content Platforms, is looking for a skilled .This project involves building ML capabilities for a user-facing product, including accelerating the ML develop...Show moreLast updated: 30+ days ago
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Machine Learning Engineer

Machine Learning Engineer

BASELAYERSan Francisco, CA, United States
1 day ago
Job type
  • Full-time
Job description

Machine Learning Engineer

Trusted by 2,200+ financial institutions, Baselayer is the intelligent business identity platform that helps verify any business, automate KYB, and monitor real-time risk. Baselayer's B2B risk solutions & identity graph network leverage state & federal government filings and proprietary data sources to prevent fraud, accelerate onboarding, and lower credit losses.

You want to learn from the best of the best, get your hands dirty, and put in the work to hit your full potential. You're not just doing it for the winyou're doing it because you have something to prove and want to be great. You are looking to be an impeccable machine learning engineer working on cutting-edge AI solutions.

You have 4-8 years of experience in machine learning development, working with Python and building ML models

You're comfortable working with large-scale data and enjoy optimizing performance for computationally intensive ML systems

You have a strong foundation in AI / ML fundamentals, particularly with LLMs, and are eager to experiment with emerging techniques

You prioritize responsible AI practices and model governance, especially in regulated environments like KYC / KYB

You have a keen eye for detail and take pride in writing clean, maintainable code while optimizing for model performance

You thrive in a high-trust, ownership-focused environment and are comfortable working across different levels of abstraction

Problem-solver who navigates the unknown confidently

Proactive self-starter who thrives in dynamic settings

Incredibly intelligent and clever. You take pride in your models

Highly feedback-oriented. We believe in radical candor and using feedback to get to the next level

Responsibilities :

Model Development & Integration : Build and maintain ML models and integrate them with various data sources, ensuring scalability, high performance, and adaptability for autonomous agents in the GTM space

ML System Design : Architect and design core ML services that support KYC / KYB processes, leveraging knowledge graphs and LLMs for dynamic use cases

Data Processing & Feature Engineering : Develop and maintain robust data pipelines for feature extraction and transformation, focusing on scalability and performance when handling large-scale, high-dimensional data

Advanced ML Techniques : Implement and experiment with state-of-the-art techniques including reinforcement learning from human feedback (RLHF) and parameter-efficient fine-tuning methods (e.g., LoRA) to improve LLMs for specific use cases within the identity space

ML Infrastructure : Build and maintain infrastructure for model training, evaluation, and deployment, creating a scalable platform foundation for continued innovation

Model Governance & Compliance : Ensure ML systems meet industry standards for fairness, explainability, and compliance, particularly around KYC / KYB regulations

Performance Optimization : Implement optimizations for model inference and training, ensuring ML services can efficiently process identity data while maintaining reliability

Experimentation & Evaluation : Design and conduct experiments to evaluate model performance, debug issues, and monitor ML services, while continuously improving architectures to handle diverse data and use cases

Work Location :

Hybrid in SF. In office 3 days / week

Compensation and Benefits :

Salary range of $145,000 to $225,000

Equity package

Unlimited vacation

Fully paid health insurance, dental, and vision

401(k) with company match