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Home Based Python Machine Learning Jobs (NOW HIRING)

Quantum Machines

Machine Learning Engineer

Chicago, IL · On-site

We are looking for a Machine Learning Engineer to design, build, and deploy machine learning ... Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

Performance-based bonuses to reward your contributions* * Paid time off to recharge and maintain a ... Python Ability to work with multiple data sources and types (structured/semi-structured ...

Pattern AI

Machine Learning Engineer

San Mateo, CA

Company Description PatternAI is an automated machine learning platform that reveals critical ... Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas) * Broad familiarity with ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical ... Fluency in Python coding as well as data manipulation (SQL, Spark, Pandas) * Broad familiarity with ...

Intraedge

Machine Learning Engineer

Sunrise, FL · On-site

Strong python, have work experiment on LLM, gen AI, Lang chain, Lang Graph, Python API, Google ... Implement short-term and long-term memory strategies for LLM-based systems. Optimize prompts ...

Rock Connections

Machine Learning Engineer

Detroit, MI · On-site +1

$107K - $241K/yr

Strong object-oriented programming skills, including proficiency in Java, Scala, C/C++ or Python ... Today,we'rea Detroit-based, publicly traded company with a mission to Help Everyone Home. At Rocket ...

TEKsystems

Machine Learning Engineer

San Diego, CA · Hybrid

$70 - $95/hr

Production Machine Learning Deployments * Model Monitoring, Observability, and Optimization ... Build Python-based tools and automation supporting ML operations and orchestration * Implement ...

Machina Labs

Machine Learning Engineer

Los Angeles, CA

$160K - $190K/yr

Write clean, well-documented, and production-quality Python code. * Communicate findings, results ... Duties and responsibilities may change based on business needs. The base salary range for this role ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Write clean, well-documented, and production-quality Python code. * Communicate findings, results ... Duties and responsibilities may change based on business needs. $160,000 - $190,000 a year The base ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

Required : • Expertise in Python (including NumPy, pandas, and other packages) • Experience with either PyTorch or TensorFlow • Deep understanding of machine learning fundamentals (gradient ...

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Title - Machine Learning ( F2F interview is required) Location - New York, NY ( Hybrid 2-3 days ... Proficient in Python, Pandas, NumPy, Scikit-Learn, PySpark Bachelor s degree in Computer Science ...

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All JobsHome Based Python Machine Learning Jobs

Home Based Python Machine Learning information

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

As of Jul 11, 2026, the average hourly pay for home based python machine learning in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 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.

More about Home Based Python Machine Learning jobs
What cities are hiring for Home Based Python Machine Learning jobs? Cities with the most Home Based Python Machine Learning job openings:
What are the most commonly searched types of Python Machine Learning jobs? The most popular types of Python Machine Learning jobs are:
What states have the most Home Based Python Machine Learning jobs? States with the most job openings for Home Based Python Machine Learning jobs include:
What job categories do people searching Home Based Python Machine Learning jobs look for? The top searched job categories for Home Based Python Machine Learning jobs are:
Home Based Python Machine Learning jobs near you
Infographic showing various Home Based Python Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 14% Part Time, and 6% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.

Machine Learning Engineer

Quantum Machines

Chicago, IL • On-site

Full-time

Posted 12 hours ago

Job description

Description
Quantum Machines (QM) is a global leader in quantum computing control systems. Through our pioneering hardware and software solutions based on instruction-based quantum control, we're revolutionizing how quantum computers are built and controlled. As we stand at the forefront of exponential growth in quantum computing, we're assembling an elite team that actively shapes the evolution of quantum technologies.
We are looking for a Machine Learning Engineer to design, build, and deploy machine learning systems that improve the calibration, control, and operation of quantum processors. In this role, you will work at the intersection of machine learning, quantum physics, and software engineering, translating noisy, non-stationary, safety-critical control problems into ML solutions that run on real hardware in production labs.
You will develop reinforcement learning policies, Bayesian inference methods, and agentic frameworks that make quantum control more autonomous, more sample-efficient, and more robust to drift. This position offers unprecedented exposure to diverse qubit types and quantum architectures, with a tight feedback loop between your models and the systems they steer, and the opportunity to deliver groundbreaking ML-driven solutions to the labs and companies defining the next generation of quantum systems.
Responsibilities:
  • Develop reinforcement learning, Bayesian inference, and probabilistic modelling approaches for parameter tuning, drift tracking, and adaptive measurement, to be deployed on real hardware.
  • Develop real-time parameter steering for calibration during QEC and between circuits.
  • Develop and maintain agentic frameworks for autonomous system control and calibration.
  • Develop and maintain Python-based ML services and libraries that integrate with the wider Quantum Machines control stack, including QUA, Qualibrate, and the OPX1000.
  • Work directly with customers and partner labs to deploy, validate, and iterate on ML solutions in real experimental environments.
  • Collaborate cross-functionally with product, R&D, and hardware teams, contributing to internal libraries, customer-facing SDKs, and training materials.

Requirements
  • PhD/Master in Machine Learning, Physics, Applied Physics, Quantum Information Science, or a related field. 4+ years of relevant experience
  • Strong background in Machine Learning and Deep Learning, with hands-on experience in at least one of: deep learning, reinforcement learning, agentic AI
  • Strong Python proficiency, including scientific or systems-oriented codebases
  • Solid software engineering fundamentals (architecture, Git workflows, testing, code review)
  • Proven track record of taking ML from prototype to deployment under real-world constraints - non-stationary data, expensive evaluations, or safety-critical action spaces. Robotics, online control, autonomous vehicles, or hardware-in-the-loop ML all transfer well
  • Strong problem-solving skills and customer-focused mindset; ability to work independently and in multidisciplinary teams
  • Proven software development track record and excellent technical communication skills
  • Familiarity with quantum computing concepts - qubit calibration, randomized benchmarking, QEC, optimal control- advantage
  • Experience with sim-to-real, multi-objective RL, or meta-learning- advantage

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