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Ai Optimization Jobs in Minnesota (NOW HIRING)

Gopher is looking for an experienced content writer with SEO/AI expertise to join our team and support the execution of digital content plans. This role will be a key member of the Digital Presence ...

Gopher is looking for an experienced content writer with SEO/AI expertise to join our team and support the execution of digital content plans. This role will be a key member of the Digital Presence ...

Gopher is looking for an experienced content writer with SEO/AI expertise to join our team and support the execution of digital content plans. This role will be a key member of the Digital Presence ...

Head of AI Solutions This role operates across innovation, execution, governance, and ... Own delivery of measurable outcomes, including revenue growth, cost optimization, efficiency gains ...

Head of AI Delivery

Minneapolis, MN · On-site

$221K/yr

Head Of Ai Solutions This role operates across innovation, execution, governance, and ... Own delivery of measurable outcomes, including revenue growth, cost optimization, efficiency gains ...

As our AI Engineer , you'll keep the AI infrastructure our products and teams run on fast ... A track record of optimizing inference performance and efficiency (latency, throughput, GPU ...

As our AI Engineer , you'll keep the AI infrastructure our products and teams run on fast ... A track record of optimizing inference performance and efficiency (latency, throughput, GPU ...

As our AI Engineer , you'll keep the AI infrastructure our products and teams run on fast ... A track record of optimizing inference performance and efficiency (latency, throughput, GPU ...

Showing results 21-40

Ai Optimization information

What are the key skills and qualifications needed to thrive as an AI optimization specialist, and why are they important?

To thrive as an AI Optimization Specialist, you need a strong background in computer science, mathematics, and machine learning, often supported by a degree in a related field. Proficiency with programming languages like Python, optimization frameworks (such as TensorFlow or PyTorch), and knowledge of cloud platforms are typically required, along with relevant certifications. Analytical thinking, problem-solving, and effective communication are essential soft skills for translating complex data into actionable solutions. These skills ensure the development of efficient, scalable AI models that drive business value and innovation.

What is the difference between Ai Optimization vs Data Scientist?

AspectAi OptimizationData Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML frameworksDegree in Statistics, Computer Science, or related fields; proficiency in programming and statistical analysis
Work EnvironmentTech companies, AI-focused teams, R&D departmentsResearch institutions, tech firms, finance, healthcare
Employer & Industry UsagePrimarily in AI development, machine learning optimization projectsData analysis, predictive modeling, data-driven decision making

Ai Optimization specialists focus on enhancing AI models' performance and efficiency, often working on machine learning algorithms and deployment. Data Scientists analyze large datasets to extract insights, build predictive models, and support decision-making. While both roles require strong technical skills and knowledge of data and algorithms, Ai Optimization is more specialized in refining AI systems, whereas Data Scientists have a broader scope in data analysis and interpretation.

What are common challenges faced by professionals in AI optimization roles, and how can they be overcome?

Professionals in AI Optimization often encounter challenges such as balancing model accuracy with computational efficiency, handling large and complex datasets, and staying updated with rapidly evolving algorithms. To overcome these, it's important to collaborate closely with data engineers and domain experts, utilize scalable computing resources, and continuously invest in learning new optimization techniques. Participating in knowledge-sharing forums and leveraging open-source tools can also help address these challenges effectively.
What are popular job titles related to Ai Optimization jobs in Minnesota? For Ai Optimization jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Ai Optimization jobs? Cities in Minnesota with the most Ai Optimization job openings:
Infographic showing various Ai Optimization job openings in Minnesota as of August 2026, with employment types broken down into 81% Full Time, 16% Part Time, and 3% Contract. Highlights an 67% Physical, 4% Hybrid, and 29% Remote job distribution.

Bioinformatics Research Scientist - AI Reviewer

micro1 AI

Rochester, MN • 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.