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Remote Validation Engineer Jobs in Connecticut (NOW HIRING)

Remote micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their ... Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank ...

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Remote Validation Engineer information

What are the typical day-to-day responsibilities of a remote validation engineer?

Remote Validation Engineers are responsible for developing and executing test plans, analyzing results, and documenting findings to ensure products meet required standards and specifications. They often collaborate virtually with design, development, and quality teams to identify issues and recommend improvements. Daily tasks may include running automated tests, preparing validation reports, participating in team meetings, and troubleshooting system behaviors. Adapting to shifting project requirements and effectively communicating in a remote setting are also integral parts of the role.

What are the key skills and qualifications needed to thrive as a remote validation engineer, and why are they important?

To thrive as a Remote Validation Engineer, you need a strong background in engineering or computer science, expertise in validation protocols, and experience with testing methodologies. Familiarity with validation tools such as simulation software, automated test platforms, and knowledge of industry compliance standards (e.g., ISO, FDA, or automotive standards) is typically required, and certifications like ISTQB can be beneficial. Excellent problem-solving skills, attention to detail, and strong written and verbal communication are important for collaborating across distributed teams. These skills ensure the effectiveness and reliability of complex products or systems while supporting seamless teamwork in a remote work environment.

What is a remote validation engineer?

A Remote Validation Engineer is responsible for testing and verifying that products, systems, or software meet required specifications and function correctly. They develop test plans, run simulations, analyze data, and document results—all while working remotely. This role is common in industries like automotive, semiconductor, and software development, ensuring quality and compliance with standards. Strong technical skills, attention to detail, and proficiency with validation tools are essential.

What are the most commonly searched types of Validation Engineer jobs in Connecticut? The most popular types of Validation Engineer jobs in Connecticut are:
What are popular job titles related to Remote Validation Engineer jobs in Connecticut? For Remote Validation Engineer jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Remote Validation Engineer jobs in Connecticut look for? The top searched job categories for Remote Validation Engineer jobs in Connecticut are:
What cities in Connecticut are hiring for Remote Validation Engineer jobs? Cities in Connecticut with the most Remote Validation Engineer job openings:
Infographic showing various Remote Validation Engineer job openings in Connecticut as of August 2026, with employment types broken down into 8% Internship, 67% Full Time, and 25% Contract. Highlights an 100% Remote job distribution.

Bioinformatics Software Engineer

micro1 AI

Hartford, CT • Remote

$80 - $110/hr

Part-time

Posted 9 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.