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Remote Machine Learning Engineer Jobs in California

As an ML Engineer, you'll help translate business and security needs into concrete ML problems, build models and features, and take them into production. You'll be part of a team working on ...

As an ML Engineer, you'll help translate business and security needs into concrete ML problems, build models and features, and take them into production. You'll be part of a team working on ...

Lead Machine Learning Engineer

Millbrae, CA · On-site +1

$119K - $156K/yr

... key engineering leadership role -- Minimum Requirements: * Doctorate in a related field * 8+ years of experience (including any applicable work in grad school) developing machine learning ...

... machine-generated data - including logs, time series, traces, and events. We combine deep AI ... Partner with executive leadership, engineering, product, and data science teams to ensure AI ...

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Remote Machine Learning Engineer information

See California salary details

$31.1K

$127.1K

$191K

How much do remote machine learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for remote machine learning engineer in California is $127,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually. High compensation often reflects expertise, leadership roles, or working in competitive industries such as tech or finance, especially in organizations valuing AI development.

What are some typical challenges faced by Remote Machine Learning Engineers, and how are they addressed?

Remote Machine Learning Engineers often face challenges such as coordinating across different time zones, ensuring smooth communication with team members, and accessing large datasets or secure environments remotely. Organizations commonly address these by using robust collaboration tools (like Slack, GitHub, and Jira), establishing clear documentation, and setting regular virtual meetings to maintain alignment. Many companies also provide secure remote environments or VPN access for handling sensitive data and code. Proactive communication and organized workflows help mitigate these challenges, enabling engineers to remain productive and connected to their teams.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $500,000 or more annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role is unlikely to be fully replaced by AI itself. Instead, AI tools can augment their work by automating routine tasks, allowing MLEs to focus on complex problem-solving, model optimization, and system integration. Continuous learning and expertise in programming, data handling, and model evaluation remain essential for MLEs in an evolving AI landscape.

What are the key skills and qualifications needed to thrive in the Remote Machine Learning Engineer position, and why are they important?

To thrive as a Remote Machine Learning Engineer, you need a strong background in computer science, mathematics, and experience with machine learning algorithms, typically supported by a relevant degree and prior project work. Proficiency with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and familiarity with cloud computing platforms is crucial, and certifications like AWS Certified Machine Learning can enhance your profile. Excellent communication, self-motivation, and time-management skills are also essential for collaborating across remote teams and meeting project goals. These combined technical and soft skills are vital for developing effective machine learning solutions while ensuring productivity and collaboration in a virtual work environment.

What is a Remote Machine Learning Engineer job?

A Remote Machine Learning Engineer designs, develops, and deploys machine learning models while working from a remote location. They preprocess data, train and optimize models, and integrate them into production systems. Their role often involves collaborating with data scientists, software engineers, and stakeholders to solve complex problems using AI. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and cloud computing knowledge are essential. Remote ML engineers must also communicate effectively and manage their time efficiently to work asynchronously with teams.

Can ML engineers work remotely?

Yes, many machine learning engineers work remotely, especially in roles that involve programming, data analysis, and model development using tools like Python, TensorFlow, or PyTorch. Remote work arrangements depend on the employer's policies and the specific project requirements, but it is common in the tech industry for ML engineers to work from home or other locations.
What are the most commonly searched types of Machine Learning Engineer jobs in California? The most popular types of Machine Learning Engineer jobs in California are:
What job categories do people searching Remote Machine Learning Engineer jobs in California look for? The top searched job categories for Remote Machine Learning Engineer jobs in California are:
What cities in California are hiring for Remote Machine Learning Engineer jobs? Cities in California with the most Remote Machine Learning Engineer job openings:
Infographic showing various Remote Machine Learning Engineer job openings in California as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $127,083 per year, or $61.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

Uber

San Francisco, CA • On-site, Remote

Other

Retirement

This job post has expired 1 day ago. Applications are no longer accepted.


Uber rating

6.9

Company rating: 6.9 out of 10

Based on 111 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire


Job description

**About the Role**Uber's newly formed AI Security team, part of the Core Security Engineering organization, is building the foundation for dynamic, data-driven security systems. We're evolving Uber's Zero Trust Architecture (ZTA) to be more risk-adaptive across authentication and authorization, moving beyond static rules and manual approvals toward real-time, ML-driven access decisions that secure both humans and AI agents.As an ML Engineer, you'll help translate business and security needs into concrete ML problems, build models and features, and take them into production. You'll be part of a team working on greenfield projects at the intersection of ML, security, and infrastructure, shaping how Uber secures AI at scale.**What the Candidate Will Need / Bonus Points**\-\-\-\- What the Candidate Will Do ----1

Support framing business and security problems as ML tasks.2. Build and iterate ML models that enable risk-adaptive, real-time decisions.3. Engineer features from Uber's risk systems, logs, and contextual signals.4

Deploy and maintain ML pipelines in production, ensuring reliability and scalability.5. Collaborate with senior engineers to integrate ML into Uber's authentication and authorization systems.\-\-\-\- Basic Qualifications ----1. 3+ years experience building and deploying ML models in production, with hands-on work in feature engineering, training, and evaluation.2

Proficiency in Python and ML frameworks (PyTorch, TensorFlow, or similar).3. Strong foundation in ML algorithms: tree-based models (XGBoost, LightGBM), classical methods (logistic regression, SVMs), and exposure to neural networks (CNNs, RNNs, Transformers).4. Ability to analyze business/security requirements and support translating them into ML use cases.\-\-\-\- Preferred Qualifications ----1

Experience with risk, fraud, anomaly detection, or security-related ML systems.2. Familiarity with large-scale data/infra systems (Kafka, Hive, Spark, Flink, Pinot).3. Exposure to handling challenges such as imbalanced data, feedback loops, or iterative retraining.4

Strong communication skills and ability to work cross-functionally with infra, risk, and security teams.For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits

More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits).Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.Uber is proud to be an Equal Opportunity employer

All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).Offices continue to be central to collaboration and Uber's cultural identity

Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.


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