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Research Python Jobs in Farmington, MI (NOW HIRING)

Waltonen

C++ / Python Programmer

Warren, MI · On-site

Research and implement emerging tools, frameworks, and technologies. Qualifications: * Bachelor ... Strong programming skills in Python, C / C++, Java, etc. * Experience with AI/ML technologies, APIs ...

Waltonen

C++ / Python Programmer

Warren, MI · On-site

Research and implement emerging tools, frameworks, and technologies. Qualifications: * Bachelor ... Strong programming skills in Python, C / C++, Java, etc. * Experience with AI/ML technologies, APIs ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

How to Apply Please send a CV and research summary to [email protected] Job Summary The College of ... Programming skills in Python or R are desired. Modes of Work Positions that are eligible for hybrid ...

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$84

How much do research python jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for research python in Farmington, MI is $57.68, according to ZipRecruiter salary data. Most workers in this role earn between $47.55 and $65.53 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.
Research Python jobs near you

Software Engineer II - Python

Rocket Close, LLC

Detroit, MI • On-site, Remote

Full-time

Posted 5 days ago

Job description

As a Python Engineer on our Data Science team, you will be at the forefront of our most ambitious technical initiatives. Your role is dual-purposed: you will build and orchestrate next-generation Agentic AI systems using AgentCore and LangGraph, and you will act as a Machine Learning Engineer (MLE) to productionize the sophisticated models developed by our Data Scientists.
We don't just follow industry trends; we aim to set them. You will be expected to be a perpetual student of the field, constantly researching and implementing the newest technologies to ensure our platform remains world-class.
Minimum Qualifications
  • Master's degree in Computer Science, Software Development, Machine Learning, or a related field, OR equivalent professional experience (3-5+ years in production-level engineering).
  • Expert-level proficiency in Python with a focus on building distributed, scalable cloud-native services.
  • Proven experience in a Data Science or Machine Learning environment, specifically in bridging the gap between research code and production software.

Preferred Qualifications
Agentic AI & Orchestration:
  • Hands-on experience with AgentCore runtime for building and managing autonomous agents.
  • Extensive experience using LangGraph to create complex, stateful multi-agent orchestrations with high visibility.
  • Deep familiarity with Amazon Bedrock, OpenAI, or Anthropic APIs and the latest advancements in LLM reasoning.
  • Experience building and optimizing RAG (Retrieval-Augmented Generation) pipelines.

Machine Learning Engineering (MLE):
  • Proven track record of productionizing Data Science models, transforming research-grade code into high-performance, scalable APIs (e.g., using FastAPI).
  • Experience with the full MLOps lifecycle: model deployment, versioning, and performance monitoring.
  • Familiarity with Amazon SageMaker or other cloud-based ML platforms.

Cloud & Infrastructure (AWS):
  • Expertise in the AWS ecosystem: Lambda (Serverless), Step Functions, ECS/EKS (Containers), EventBridge, and S3.
  • Strong proficiency in Infrastructure as Code (IaC) using Terraform.
  • Experience building asynchronous, event-driven architectures.

Observability & Engineering Excellence:
  • Proficiency in Splunk and CloudWatch for production monitoring and alerting.
  • Strong knowledge of software development life cycle (SDLC) processes, including unit testing, regression testing, and Agile concepts.
  • Ability to work with broad, loosely developed concepts and translate them into precise technical specifications.

Key Responsibilities
  • Agentic AI Innovation: Design and implement autonomous agents using AgentCore and orchestrate them via LangGraph to ensure complex workflows are visible and manageable.
  • MLE Productionization: Partner with Data Scientists to take ML models from research notebooks into scalable, production-ready AWS environments.
  • Constant Research: Proactively research, test, and present the newest technologies, frameworks, and AI research papers to the team. You are expected to be an early adopter of tools that can improve our velocity or service quality.
  • System Architecture: Build and maintain the cloud-native infrastructure (AWS) required for AI/ML inference and agentic execution, ensuring high availability and cost-efficiency.
  • Observability: Implement deep monitoring and alerting for all services, using LangGraph for agent-specific visibility and Splunk for broader system health.
  • Code Quality: Participate in rigorous code reviews and help define the engineering standards for the Data Science team.
  • Collaboration: Work without complete specifications to help derive technology solutions that meet the evolving needs of the business.

What you'll get
Our team members fuel our strategy, innovation and growth, so we ensure the health and well-being of not just you, but your family, too! We go above and beyond to give you the support you need on an individual level and offer all sorts of ways to help you live your best life. We are proud to offer eligible team members perks and health benefits that will help you have peace of mind. Simply put: We've got your back. Check out our full list of Benefits and Perks.
On-Call Expectations
This role may include participation in an on-call rotation to support production systems and ensure service reliability. On-call responsibilities may include coverage during nights and weekends. If applicable, frequency and scheduling will be determined by team needs and communicated accordingly.
About us
Rocket Close is a leading national provider of title insurance, property valuations and settlement services. Here, you'll be given all the resources and support needed to deliver innovative solutions and in turn, your hard work will be rewarded with a competitive compensation package and an array of other amazing benefits. Apply today to join a team that offers career growth, amazing benefits and the chance to work with leading industry professionals.
This job description is an outline of the primary responsibilities of this position and may be modified at the discretion of the company at any time. Decisions related to employment are not based on race, color, religion, national origin, sex, physical or mental disability, sexual orientation, gender identity or expression, age, military or veteran status or any other characteristic protected by state or federal law. The company provides reasonable accommodations to qualified individuals with disabilities in accordance with applicable state and federal laws. Applicants requiring reasonable accommodations in completing the application and/or participating in the application process should contact a member of the Human Resources team, at Careers@Rocket.com.

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