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Home Based Python Machine Learning Jobs in Mountain View, CA

Deepproficiencyin programming languages such as Python, Java, or similar, with a strong emphasis on ... Experiencebuilding LLM-based AI agent workflows via both no code/low code and traditional high-code ...

Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and ... based Generative AI and transformer architecture. * Skilled in communication, problem solving ...

This is a fully on-site role based in Manteno, IL focused on building innovative ML models from the ... Proficiency in Python and ML libraries/frameworks such as PyTorch, TensorFlow, etc. * Solid ...

... and performance evaluationProficiency in Python for algorithm development and ... and iterate based on experimental resultsExperience owning algorithm development from early ...

Software engineering skills and proficiency in Python.Experience with PyTorch.BA/BS degree in computer vision, computer graphics, machine learning or related field. MS or PhD in computer vision ...

... Python. Experience with one of the following: machine learning/deep learning systems, computer ... vision, graphics, computational imaging applications. Experience with Pytorch. Pay & Benefits At ...

Lead the ML organization, consisting of multiple teams, to design, develop, and optimize ML-based ... Advanced knowledge of Python, SQL * Strong oral and written communication skills #LI-Hybrid

... Go, Python, Rust, Java, C++, Ruby, etc...) • Experience working with high volumes of data, ideally with machine learning playing a critical role • Strong foundational knowledge of mathematics ...

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Home Based Python Machine Learning information

See Mountain View, CA salary details

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How much do home based python machine learning jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for home based python machine learning in Mountain View, CA is $69.15, according to ZipRecruiter salary data. Most workers in this role earn between $57.02 and $78.56 per hour, depending on experience, location, and employer.

What is the difference between Home Based Python Machine Learning vs Data Analyst?

AspectHome Based Python Machine LearningData Analyst
Required CredentialsPython programming, machine learning certifications, data analysis skillsData analysis certifications, SQL, Excel, Python or R knowledge
Work EnvironmentRemote, home-based, often project-focusedRemote or on-site, business or client-focused
Industry UsageTech, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare
Common Search/ComparisonYesYes

Home Based Python Machine Learning and Data Analyst roles share overlapping skills like data handling and analysis tools. However, Python Machine Learning focuses more on developing algorithms and models using Python, while Data Analysts primarily interpret data to generate reports and insights. Both roles are in demand for remote work and require analytical skills, but Python Machine Learning positions often demand more advanced programming and machine learning expertise.

What are popular job titles related to Home Based Python Machine Learning jobs in Mountain View, CA? For Home Based Python Machine Learning jobs in Mountain View, CA, the most frequently searched job titles are:
What job categories do people searching Home Based Python Machine Learning jobs in Mountain View, CA look for? The top searched job categories for Home Based Python Machine Learning jobs in Mountain View, CA are:
What cities near Mountain View, CA are hiring for Home Based Python Machine Learning jobs? Cities near Mountain View, CA with the most Home Based Python Machine Learning job openings:

Machine Learning Engineer

RZR Global Inc.

San Francisco, CA

Other

Posted 12 days ago


Job description

Who are we?

RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.
The role?

We are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.

What will you do?
  • Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
  • Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
  • Analyze the impact of integrating new data sources and features into our models.
  • Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
  • Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
  • Document experiments, assumptions, and outcomes; maintain reproducibility
What are we looking for?
  • Bachelor's degree in Mathematics, Physics, Computer Science, or a related technical field.
  • At least 2 years of professional experience in machine learning, statistical analysis, and data analysis.
  • Experience with machine learning techniques such as regression, classification, and clustering.
  • Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
  • Strong grasp of probability, statistics, and data analysis principles.
  • Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.
Nice-to-Have
  • Familiarity with system programming languages including C++ and Rust is a plus.
  • Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
  • Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.