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Remote Machine Learning Jobs in Berkeley, CA (NOW HIRING)

Senior Machine Learning Engineer

San Francisco, CA ยท On-site +1

$186.10K - $300.55K/yr

What you'll do We are looking for a Senior Machine Learning Engineer to redefine how we operate our ... Employee divides their time between in-office and remote work. Access to an office location is ...

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Remote Machine Learning information

See Berkeley, CA salary details

$31.2K

$52.1K

$107.8K

How much do remote machine learning jobs pay per year?

As of May 31, 2026, the average yearly pay for remote machine learning in Berkeley, CA is $52,141.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,800.00 and $56,300.00 per year, depending on experience, location, and employer.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

Is ML full of coding?

Machine Learning (ML) roles often involve significant coding, especially in programming languages like Python or R, to develop algorithms and models. However, some positions focus more on data analysis, feature engineering, or model evaluation, which may require less coding but still involve technical skills and understanding of ML concepts.

What is the difference between Remote Machine Learning vs Data Scientist?

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Machine Learning jobs in Berkeley, CA? The most popular types of Machine Learning jobs in Berkeley, CA are:
What job categories do people searching Remote Machine Learning jobs in Berkeley, CA look for? The top searched job categories for Remote Machine Learning jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Remote Machine Learning jobs? Cities near Berkeley, CA with the most Remote Machine Learning job openings:
Infographic showing various Remote Machine Learning job openings in Berkeley, CA as of May 2026, with employment types broken down into 1% Internship, 1% As Needed, 46% Full Time, 50% Part Time, 1% Temporary, and 1% Contract. Highlights an 72% Physical, and 28% Remote job distribution, with an average salary of $52,141 per year, or $25.1 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

DocuSign

San Francisco, CA โ€ข On-site, Remote

$186.10K - $300.55K/yr

Full-time

Medical, Life, Retirement, PTO

Posted yesterday


Job description

Company Overview

Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people's lives. With intelligent agreement management, Docusign unleashes business-critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign's Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM).

What you'll do

We are looking for a Senior Machine Learning Engineer to redefine how we operate our global services. You won't just be building dashboards; you will be building the "brain" of our infrastructure.

We are moving beyond simple anomaly detection. We are building a self-healing ecosystem where Multi-Agent Systems and Reinforcement Learning (RL) loops work in tandem with Large Language Models (LLMs) to not only detect incidents in real-time but to troubleshoot and resolve them autonomously.

If you are passionate about applying complex AI architectures to massive datasets (billions of telemetry points) to solve real-world reliability challenges, this is the role for you.

This position is an individual contributor role reporting to the Sr. Director, Software Engineering.

Responsibility

  • Design and implement autonomous multi-agent systems using Reinforcement Learning (RL) loops that can interact with our infrastructure to perform safe, automated remediation actions

  • Build GenAI agents capable of digesting logs, traces, and metrics to provide "Human-in-the-loop" root cause analysis and conversational debugging for our SREs

  • Develop and deploy deep learning models (Transformers, LSTMs, etc.) for forecasting and anomaly detection on high-cardinality, high-volume time series data

  • Optimize inference pipelines to run with low latency on streaming telemetry data (Kafka/Flink), ensuring we catch issues the moment they happen

  • Own the lifecycle of your models-from feature engineering on petabyte-scale datasets to training, deployment, and monitoring in production Kubernetes environments

  • Collaborate with Applied Scientists to translate bleeding-edge research (e.g., causal inference, decision transformers) into production-hardened AIOps tools

Job Designation

Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)

Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.

What you bring

Basic

  • 8+ years of professional experience in Machine Learning Engineering or Data Science

  • Experience with PyTorch or TensorFlow, specifically regarding Time Series analysis (forecasting/anomaly detection) and NLP

  • Experience building applications using LLMs (RAG pipelines, LangChain, vector databases) specifically for technical domains (code analysis, log parsing)

  • Experience with RL concepts (policies, rewards, agents) and experience applying them to optimization or control problems

  • Experience with distributed data processing and streaming technologies (Apache Spark, Kafka, Flink)

  • Expereience with software engineering fundamentals (Python, C++, or Go), CI/CD for ML, and experience deploying models via APIs (FastAPI, Triton Inference Server)

Preferred

  • Familiarity with the "three pillars" (Logs, Metrics, Traces) and tools like Prometheus, Grafana, OpenTelemetry, or Jaeger

  • Experience with frameworks like AutoGen, CrewAI, or Ray RLlib

  • Deep experience with AWS/GCP/Azure and Kubernetes (K8s) orchestration

  • A background in control theory or causal inference

Wage Transparency

Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.

Based on applicable legislation, the below details pay ranges in the following locations:

California: $186,100.00 - $300,550.00 base salary

Washington, Maryland, New Jersey and New York (including NYC metro area): $178,900.00 - $262,825.00 base salary

This role is also eligible for the following:

  • Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre-established sales goals. Non-Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance.
  • Stock: This role is eligible to receive Restricted Stock Units (RSUs).

Global benefits provide options for the following:

  • Paid Time Off: earned time off, as well as paid company holidays based on region
  • Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement
  • Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment
  • Retirement Plans: select retirement and pension programs with potential for employer contributions
  • Learning and Development: options for coaching, online courses and education reimbursements
  • Compassionate Care Leave: paid time off following the loss of a loved one and other life-changing events
Life at DocuSign

Working here

Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what's right, every day. At Docusign, everything is equal.

We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you'll be loved by us, our customers, and the world in which we live.

Accommodation

Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com.

If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance.

Applicant and Candidate Privacy Notice

States Not Eligible for Employment

This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming.

EEO Statement

It's important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can-do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category.

EEO Know Your Rights poster

Employment Type: FULL_TIME