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Research Python Jobs in Austin, TX (NOW HIRING)

SEMRON

ML Research Scientist

Austin, TX · On-site

... Python and PyTorch, with the ability to rapidly prototype and evaluate research ideas • A research mindset: curiosity, rigor, and the ability to explore and discard ideas efficiently Preferred ...

Senseye

Research Data Analyst

Austin, TX

Use Python and AI-assisted coding tools to build analysis pipelines and statistical tests ... A solid understanding of the research workflow: experimental design, hypothesis formulation ...

Senseye

Research Data Analyst

Austin, TX · On-site

Use Python and AI-assisted coding tools to build analysis pipelines and statistical tests ... A solid understanding of the research workflow: experimental design, hypothesis formulation ...

Senseye

Research Data Analyst

Austin, TX · On-site

Use Python and AI-assisted coding tools to build analysis pipelines and statistical tests ... A solid understanding of the research workflow: experimental design, hypothesis formulation ...

webAI

AI Research Scientist

Austin, TX · On-site

... Python and ML frameworks such as PyTorch, TensorFlow, or JAX • Experience building datasets ... research tasks • Effective communication skills for presenting research findings to diverse ...

webAI Inc

AI Research Director

Austin, TX · On-site

Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or JAX * Strong research background demonstrated through publications, patents, or deployed innovations * Ability to communicate ...

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All JobsResearch Python JobsResearch Python Jobs in Austin, TX

Research Python information

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$13

$58

$85

How much do research python jobs pay per hour?

As of Aug 2, 2026, the average hourly pay for research python in Austin, TX is $58.11, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

What is a Research Python Developer?

A Research Python Developer is a professional who uses the Python programming language to support and conduct research activities. They often work with data analysis, machine learning, simulation, and automation to solve scientific or academic problems. Their role may involve developing prototypes, processing large datasets, and collaborating with researchers to implement algorithms or models. Research Python Developers are commonly found in universities, research institutions, and tech companies focused on innovation.

Is Python good for research?

Research Python developers use Python because of its simplicity, extensive libraries, and strong support for data analysis, machine learning, and scientific computing. It is widely adopted in academia and industry for research projects, often complemented by tools like Jupyter notebooks and frameworks such as NumPy and pandas.

What Python jobs are in demand?

Python development roles such as data scientist, machine learning engineer, backend developer, and automation engineer are currently in high demand. These positions often require knowledge of frameworks like Django or Flask, data analysis libraries, and proficiency in cloud platforms. Demand is driven by industries including technology, finance, healthcare, and e-commerce, with many roles requiring strong problem-solving skills and experience with version control tools like Git.

Will AI replace Python coders?

Research Python coders develop and maintain Python-based applications and tools, and while AI can automate certain coding tasks, it is unlikely to fully replace human programmers due to the need for problem-solving, creativity, and understanding complex requirements. AI tools can assist coders by increasing efficiency and handling repetitive tasks, but human oversight remains essential for quality and innovation.

What is the difference between Research Python vs Data Analyst?

AspectResearch PythonData Analyst
Required SkillsPython programming, research methodologies, data analysisData analysis, visualization, SQL, Excel
Work EnvironmentResearch labs, academic institutions, tech companiesBusiness settings, corporate offices, consulting firms
Common CertificationsPython certifications, research methodology coursesMicrosoft Excel, Tableau, SQL certifications
Industry UsageAcademic research, scientific projects, tech R&DBusiness intelligence, marketing, finance

Research Python focuses on using Python for scientific and academic research, emphasizing programming and research methodologies. Data Analysts primarily analyze and interpret data to support business decisions, often using tools like Excel and Tableau. While both roles require data skills, Research Python is more technical and research-oriented, whereas Data Analysts focus on data interpretation within business contexts.

What are the key skills and qualifications needed to thrive as a Research Python Developer, and why are they important?

To thrive as a Research Python Developer, you need expertise in Python programming, data analysis, and a strong foundation in mathematics or computer science, often supported by an advanced degree. Familiarity with libraries such as NumPy, pandas, TensorFlow, and version control systems like Git is typically required. Analytical thinking, problem-solving, and effective communication are crucial soft skills for translating research goals into practical code. These skills are essential for developing robust research solutions, collaborating with interdisciplinary teams, and advancing scientific or technical projects.

What are some common challenges faced by Research Python Developers when collaborating with cross-functional teams?

Research Python Developers often work alongside data scientists, domain experts, and engineers, which can present challenges such as aligning on project goals, translating research requirements into efficient code, and ensuring reproducibility of results. Effective communication and thorough documentation are key to overcoming these challenges. Additionally, Research Python Developers may need to adapt their code to integrate with different tools or platforms used by other team members, requiring flexibility and a willingness to learn new technical concepts.

Is Python still in demand in 2026?

Python remains a highly in-demand skill for research roles, including those involving data analysis, machine learning, and automation. Its versatility, extensive libraries, and widespread use in industry and academia ensure continued demand for professionals proficient in Python in 2026.
What are popular job titles related to Research Python jobs in Austin, TX? For Research Python jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Research Python jobs in Austin, TX look for? The top searched job categories for Research Python jobs in Austin, TX are:
What cities near Austin, TX are hiring for Research Python jobs? Cities near Austin, TX with the most Research Python job openings:
Research Python jobs near you
Infographic showing various Research Python job openings in Austin, TX as of June 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 82% Physical, 6% Hybrid, and 12% Remote job distribution, with an average salary of $120,861 per year, or $58.1 per hour.

Electrical Engineer with Python Proficiency - AI Trainer

Kake Group

Austin, TX • Remote

Contractor

Re-posted 15 days ago

Job description

We're building a talent pool of Electrical Engineering professionals with Python proficiency to contribute to project-based AI development initiatives, focused on evaluating and enhancing frontier AI models.

Designed for electrical engineers who enjoy deep technical problem-solving, this pipeline role is for those looking to apply their simulation expertise to evaluate and push the boundaries of frontier AI models, relying on domain-specific tools such as ngspice, scikit-rf, python-control, or pandapower, with verifiable, code-graded answers run inside isolated Linux environments.

Key Responsibilities

  • Identify an appropriate electrical engineering simulation package and build problems whose solution genuinely hinges on that tool's core capabilities, whether solvers, simulation kernels, or domain-specific models.
  • Develop full Python solutions for each problem, providing all necessary netlist files and circuit definitions as required.
  • Establish the correct numerical output and define how close the AI model needs to get, using tolerance values appropriate to the engineering context.
  • Run the problem against the AI model across multiple parallel attempts, analyzing where it succeeds or falls short, and adjusting difficulty until the pass rate falls between 10% and 30%.
  • Tune circuit topologies, operating conditions, and solver parameters iteratively, building an understanding of how the model navigates complex circuit, control, and power systems problems.
  • Hand off completed tasks to a senior reviewer in your subfield and refine based on their feedback before final submission.

Core Requirements

  • Academic background in Electrical Engineering or a closely related field.
  • At least 2 years of hands-on experience in engineering research, applied work, or teaching.
  • Solid Python skills, applied to writing and validating computational solutions.
  • Capacity to build problems that cannot be solved without specialized simulation software.
  • Excellent written and verbal communication skills in English.
  • Ability to work independently in a remote, fast-paced environment.

Nice-to-Have

  • Working knowledge of one or more domain-specific electrical engineering tools, including but not limited to ngspice, scikit-rf, python-control, pandapower, or PyPSA, or a demonstrated ability to get up to speed independently.
  • Prior exposure to how frontier AI models approach complex simulation tasks.
  • Knowledge spanning more than one engineering domain, such as circuit analysis, control systems, or power systems.
  • Familiarity with containerized or sandboxed Linux execution environments.

Please Note: Due to the high volume of applications, only shortlisted candidates will be contacted.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.