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Home Based Python Machine Learning Jobs in Los Angeles, CA

Palo Alto Networks

Machine Learning Engineer

Encino, CA

$129.10K - $208.83K/yr

Proficiency in at least one programming language such as Python, Java, or Golang. * Experience ... Experience with cloud platforms (GCP, AWS) and container-based development (Docker, Kubernetes)

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

This position is based at Silvus Technologies' headquarters in the heart of vibrant West Los ... Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, etc.). * Exposure to ...

Wings of Destiny

Machine Learning Engineer

Malibu, CA · Remote

Role Overview We are seeking a Machine Learning Engineer (Volunteer) to help design, build, and ... Experience with Python and ML libraries such as TensorFlow, PyTorch, or scikit-learn * Familiarity ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable ... Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.

Rule14

Be Seen First

Data Scientist Machine Learning

Santa Monica, CA · On-site

$65K - $85K/yr

Select appropriate algorithms based on project requirements * Tune and optimize model performance ... Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn

Field AI

3D Machine Learning Engineer

Irvine, CA

Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable ... Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable ... Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.

FieldAI

3D Machine Learning Engineer

Irvine, CA

Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable ... Strong expertise in Python and deep learning frameworks: PyTorch, TensorFlow, or similar.

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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 Los Angeles, CA is $63.17, according to ZipRecruiter salary data. Most workers in this role earn between $52.07 and $71.73 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 Los Angeles, CA? For Home Based Python Machine Learning jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Home Based Python Machine Learning jobs in Los Angeles, CA look for? The top searched job categories for Home Based Python Machine Learning jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Home Based Python Machine Learning jobs? Cities near Los Angeles, CA with the most Home Based Python Machine Learning job openings:
Home Based Python Machine Learning jobs near you
Machine Learning Engineer

Machine Learning Engineer

Silvus Technologies

Los Angeles, CA

Other

Posted yesterday

Job description

THE OPPORTUNITY

Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team.  The successful individual in this role will focus on applying machine learning and data-driven techniques to improve the performance, efficiency, and adaptability of Silvus' advanced MIMO radios and wireless networking systems.  This individual will work closely with experts in wireless communications, DSP, networking, and embedded systems to develop ML-driven features that solve real-world problems in dynamic and challenging RF environments.

This position is based at Silvus Technologies' headquarters in the heart of vibrant West Los Angeles, CA, and is on a hybrid schedule.  A minimum of 3 days onsite per week is expected. On-site days are Mondays, Wednesdays, and Thursdays.

The following is a list of at least some of the current essential job functions of the position. Management may assign or reassign duties and responsibilities at any time at its discretion.

 ROLE AND RESPONSIBILITIES

  • Research, design, and implement machine learning algorithms to enhance performance in wireless communication systems (e.g., link adaptation, interference mitigation, anomaly detection, spectrum sensing).
  • Analyze real-world RF datasets to extract insights and develop predictive models.
  • Develop software prototypes and integrate ML algorithms with Silvus' radio firmware and networking stack.
  • Collaborate with cross-functional teams to define ML use cases and evaluate the impact of deployed models.
  • Contribute to the design of data pipelines and infrastructure for training, testing, and validating models.
  • Participate in performance benchmarking and iterative improvement cycles.
  • Stay current with the latest Machine Learning research for wireless and embedded systems.
  • Perform other related duties of which the above are representative.

REQUIRED QUALIFICATIONS

  • Bachelor of Science degree in Electrical Engineering, Computer Science, Computer Engineering, or related field plus a minimum of 2 years of experience in machine learning, with demonstrated application to real-world problems; no experience required with an advance degree (MS or PhD)
  • Strong foundation in supervised and unsupervised learning and statistical modeling.
  • Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, etc.).
  • Exposure to MATLAB or C/C++ for signal processing algorithm development.
  • Must be a U.S. Citizen due to clients under U.S. government contracts.
  • All employment is contingent upon the successful clearance of a background check and drug test.

 PREFERRED KNOWLEDGE, SKILLS, AND ABILITIES

  • MS. or Ph.D. in Electrical Engineering, Computer Science, or a related field.
  • Demonstrated experience with RF signal classification, anomaly detection, or spectrum monitoring.
  • Proficiency in MATLAB or C/C++ for signal processing algorithm development.
  • Familiarity with wireless communication concepts (e.g., PHY/MAC layers, MIMO, OFDM, spectrum access).
  • Familiarity with embedded ML, real-time systems, or deploying ML on edge devices.
  • Background in adaptive modulation, beamforming, or cognitive radio techniques.
  • Experience working with wireless standards such as 3GPP, IEEE 802.11/15, or military waveforms.
  • Experience with GPU acceleration or model optimization for constrained environments.
  • Excellent communication and collaboration skills.

WORKING CONDITIONS AND PHYSICAL REQUIREMENTS

  • Office environment.
  • Outdoor environment for demos.
  • Occasional exposure to heat, cold, and allergens while performing tests or demonstrations in the field.
  • While performing the duties of this job, the employee is required to do the following:
    • Lift equipment up to 20 lbs. for the set-up of demonstrations and testing.
    • Perform bending and reaching movements to place items on lower and higher shelves.

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