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Data Annotation Ai Training Jobs in Rhode Island

ClifyX

Data Strategy Lead

Johnston, RI · On-site

... training chatbots and other AI models, ensuring model accuracy, fairness, and scalability. • Establish and enforce data governance, quality, and compliance standards to maintain data integrity and ...

Cisco

Applied AI Scientist

Providence, RI · On-site

We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco ... Develop and enhance distributed training and inference workflows, leveraging data-driven approaches ...

Apex Systems

Senior Data Engineer-PBM

Woonsocket, RI · On-site

$109K - $131K/yr

Supports the creation and operation of Big Data AI/machine learning solutions, using complex health ... Collaborates with data science team to define and build datasets for training of analytic data ...

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Infographic showing various Data Annotation Ai Training job openings in Rhode Island as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution.

AI Training Specialist - Cheminformatics

Providence, RI • Remote

micro1 AI
Software Development • 11 - 50 employees
Learn more about micro1 AIexternal

$80 - $110/hr

Part-time

Posted 24 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.

Apply