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Remote Ai Coding Jobs in Minnesota (NOW HIRING)

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Remote Ai Coding information

What is remote AI coding?

Remote AI coding refers to the practice of developing and deploying artificial intelligence models and applications from a remote location, rather than working onsite at a company’s office. Remote AI coders use programming languages like Python, machine learning frameworks, and cloud platforms to create solutions such as chatbots, recommendation systems, and data analysis tools. This role allows professionals to collaborate with teams and clients across the globe using online communication and version control tools. Remote AI coding offers flexibility, access to a wider range of job opportunities, and the ability to work from anywhere with a reliable internet connection.

What are the key skills and qualifications needed to thrive as a remote AI coding professional?

To thrive as a Remote AI Coding professional, you need strong programming skills (especially in Python), a solid understanding of machine learning concepts, and a relevant degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, Git, and cloud platforms (e.g., AWS, Google Cloud) is typically required, along with certifications in AI or data science as a plus. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for collaborating remotely and managing independent tasks. These competencies enable efficient project delivery, innovation, and effective teamwork in a distributed work environment.

What are some common challenges faced by remote AI coding professionals, and how can they be overcome?

Remote AI coding professionals often encounter challenges such as collaborating across time zones, maintaining clear communication with team members, and managing complex projects without in-person oversight. To overcome these, it's important to establish regular check-ins using collaboration tools like Slack or Zoom, document code and project updates thoroughly, and leverage version control systems such as Git. Proactively communicating progress and blockers helps ensure alignment and smooth teamwork, even when working remotely.

What is the difference between Remote Ai Coding vs Data Scientist?

AspectRemote Ai CodingData Scientist
Required CredentialsProgramming skills, AI/ML knowledge, sometimes certificationsStatistics, programming, often advanced degrees
Work EnvironmentRemote, tech companies, AI-focused teamsRemote or on-site, diverse industries
Industry UsageTech, AI startups, software firmsFinance, healthcare, tech, research
Common Search/ComparisonYesNo

Remote Ai Coding involves developing AI algorithms and models primarily through programming, often in a remote setting within tech-focused companies. Data Scientists analyze data to extract insights, requiring statistical expertise and often working across various industries. While both roles may work remotely, Remote Ai Coding is more specialized in AI development, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Ai Coding jobs in Minnesota?

The most popular types of Ai Coding jobs in Minnesota are:

What are popular job titles related to Remote Ai Coding jobs in Minnesota?

For Remote Ai Coding jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Remote Ai Coding jobs in Minnesota look for?

The top searched job categories for Remote Ai Coding jobs in Minnesota are:

What cities in Minnesota are hiring for Remote Ai Coding jobs?

Cities in Minnesota with the most Remote Ai Coding job openings:

Remote Ai Coding jobs near you

AI Training Specialist - Cheminformatics

micro1 AI

Rochester, MN • Remote

$80 - $110/hr

Part-time

Posted 15 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

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