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Machine Learning Manager Jobs in Dublin, CA (NOW HIRING)

Sift Science, Inc

Machine Learning Engineer

San Francisco, CA · On-site

$134K - $162K/yr

As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large ... Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

... management, and Go, the proactive AI assistant that understands context and delivers help ... MS / PhD in Computer Science. * 5+ years of industry experience as a machine learning engineer or ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$180 - $260/hr

... management, and Go, the proactive AI assistant that understands context and delivers help ... MS / PhD in Computer Science. * 5+ years of industry experience as a machine learning engineer or ...

Reducto

Machine Learning Engineer

San Francisco, CA · On-site

Reducto is a rapidly growing company that helps AI teams manage unstructured enterprise data with high accuracy. They are seeking a Machine Learning Engineer to train and deploy critical models for ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

Conduct research using machine learning methodologies that integrate financial theory with deep ... We serve asset managers and owners, private-market sponsors and investors, hedge funds, wealth ...

MSCI

Machine Learning Researcher

San Francisco, CA

$144K - $187K/yr

MSCI is establishing a Machine Learning Center of Excellence within the Research & Development team ... We serve asset managers and owners, private-market sponsors and investors, hedge funds, wealth ...

Plenful

Machine Learning Engineer

San Francisco, CA · On-site

You'll partner closely with software engineers, product managers, and data teams to build models ... Design, build, and deploy machine learning models into production * Develop scalable ML pipelines ...

MSCI

Machine Learning Researcher

San Francisco, CA · On-site

$144K - $187K/yr

Conduct research using machine learning methodologies that integrate financial theory with deep ... We serve asset managers and owners, private-market sponsors and investors, hedge funds, wealth ...

Superhuman

Machine Learning Engineer

San Francisco, CA · On-site

$250K - $385K/yr

... management, and Go, the proactive AI assistant that understands context and delivers help ... MS / PhD in Computer Science. * 5+ years of industry experience as a machine learning engineer or ...

Relace

Machine Learning Engineer

San Francisco, CA · On-site

The Role We're looking for a Machine Learning Engineer who loves getting close to the metal. This ... Understanding of memory management, parallelization, and hardware-aware model optimization. * 2+ ...

Adobe Systems

Dir, Machine Learning Eng

San Jose, CA · On-site

... and management of the digital marketing tools to help our customers to easy work towards ... A deep understanding of machine learning models, frameworks, and algorithms, with hands-on ...

Stripe

Machine Learning Engineer

South San Francisco, CA · On-site +1

$212K - $318K/yr

... management for Stripe Capital based on ML principles, domain knowledge, risk, regulatory and ... Designing, training and evaluating machine learning models; * Productionizing and deploying machine ...

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Machine Learning Manager information

See Dublin, CA salary details

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$92K

$132.9K

How much do machine learning manager jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning manager in Dublin, CA is $92,020.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,300.00 and $104,200.00 per year, depending on experience, location, and employer.

What is a machine learning manager?

Machine Learning Managers are professionals responsible for leading teams that develop, implement, and maintain machine learning models and systems. They oversee data scientists, engineers, and other specialists, ensuring projects align with business goals and are delivered on time. Their role often involves coordinating cross-functional teams, managing project timelines, and staying current with the latest advancements in artificial intelligence and machine learning. Additionally, they may be involved in hiring, mentoring, and providing technical guidance to their team.

What are the key skills and qualifications needed to thrive as a machine learning manager?

To thrive as a Machine Learning Manager, you need a robust background in machine learning algorithms, statistical analysis, and software engineering, typically supported by an advanced degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and project management platforms, along with experience in deploying ML systems, is essential. Strong leadership, communication, and strategic thinking skills set exceptional managers apart, enabling them to guide teams and align projects with business objectives. These skills are crucial to successfully leading technical teams, ensuring project delivery, and translating complex ML solutions into organizational value.

What are some of the main challenges a machine learning manager faces when leading a team?

A Machine Learning Manager often navigates challenges such as balancing project deadlines with the need for thorough experimentation and research, ensuring clear communication between technical and non-technical stakeholders, and fostering collaboration among data scientists, engineers, and product teams. Additionally, managers must keep their team's skills current with rapidly evolving technologies while also addressing issues like data quality and model deployment in production environments. Successfully overcoming these challenges requires strong leadership, adaptability, and a deep understanding of both business objectives and technical intricacies.

Is machine learning a high paying job?

Machine Learning Managers typically earn high salaries due to their specialized skills in data analysis, programming, and model development. Compensation varies based on experience, location, and industry, but it is generally considered a well-paying role within the tech sector.

What are the most commonly searched types of Machine Learning jobs in Dublin, CA?

The most popular types of Machine Learning jobs in Dublin, CA are:

What are popular job titles related to Machine Learning Manager jobs in Dublin, CA?

For Machine Learning Manager jobs in Dublin, CA, the most frequently searched job titles are:

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What cities near Dublin, CA are hiring for Machine Learning Manager jobs?

Cities near Dublin, CA with the most Machine Learning Manager job openings:

Machine Learning Manager jobs near you

Machine Learning Engineer

Sift Science, Inc

San Francisco, CA • On-site

$134K - $162K/yr

Other

This job post has expired today. Applications are no longer accepted.

Job description

The Role:
As a Machine Learning Engineer at Sift, you will bridge the gap between data science and large-scale distributed systems. You won't just train models in isolation; you will build end-to-end pipelines that extract signals, train custom models per merchant, and serve predictions at production scale with low latency. You will work on an automated machine learning ecosystem that dynamically recalibrates models based on streaming global telemetry data.
What You'll Do:
  • Model Development & Refinement: Design, build, and deploy online machine learning models (including ensemble methods, deep learning, transformer architectures and graph-based models) to catch evolving fraud vectors in real time.
  • Feature Engineering at Scale: Engineer high-frequency time-series features from over 1 trillion behavioral events, optimizing for low-latency signal extraction and pattern recognition.
  • Production MLOps: Maintain and enhance our automated model training and deployment infrastructure, ensuring frictionless continuous integration and continuous deployment (CI/CD) of newly trained models.
  • System Optimization: Write high-performance code to minimize scoring latency at runtime, ensuring our core ML services scale seamlessly across distributed databases.
  • Collaborative Innovation: Work cross-functionally with Core Infrastructure, Product Management, and Data Science teams to translate business-level fraud patterns into robust algorithmic solutions.
What We Are Looking For (Requirements):
  • Experience: 4+ years of professional experience building and deploying large-scale machine learning models into high-traffic production environments.
  • Solid Programming Foundations: Strong proficiency in Java or Scala (for our production backend) as well as Python (for data analysis and model prototyping).
  • Distributed Systems & Big Data: Practical experience with Databricks and big data processing frameworks like Apache Spark, Apache Flink, or Hadoop, and working with NoSQL data stores like Bigtable.
  • Strong Mathematical Foundations: Deep understanding of statistical modeling, probability, and standard machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks, and Clustering techniques).
  • System Design Mentality: Ability to reason through data consistency, pipeline failures, and performance constraints in a distributed, multi-tenant cloud environment (Google Cloud Platform).
Bonus Points (Preferred Qualifications):
  • Experience explicitly in the fraud detection, risk mitigation, or cyber-security domains.
  • Deep knowledge of streaming architectures (e.g., Apache Kafka).
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Familiarity with leveraging AI coding assistants (e.g., Claude Code) to accelerate development and model prototyping

Please note: final stage candidates may be asked to travel for in-person final round interviews.
Let's build it together:
At Sift, we are intentionally building a diverse, equitable, and inclusive workplace. We believe that diversity drives innovation, equity is a fundamental right, and inclusion is a basic human need. We envision a place where all Sifties feel secure sharing their authentic selves and diverse experiences with their teams, their customers, and their community - ultimately using this empowerment and authenticity to build trust and create a safer Internet.
This document provides transparency around how Sift handles the personal data of job applicants: ;br>
A little about us:
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Global brands rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.

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