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Remote Machine Learning Biology Jobs in Minnesota

Dlapiper

Data Scientist

Minneapolis, MN · On-site +1

A specialization in machine-learning, artificial intelligence, cognitive science or data science is ... Opportunity for a hybrid work arrangement combining remote and in-office work. The specific ...

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Remote Machine Learning Biology information

What is a remote machine learning biologist?

A Remote Machine Learning Biologist is a professional who applies machine learning techniques to biological data and problems while working remotely, often from home or a location outside a traditional laboratory or office. They use computational tools and algorithms to analyze complex biological datasets, such as genomics, proteomics, or drug discovery data, to derive insights or make predictions. Their work may involve developing predictive models, automating data analysis, and collaborating with life scientists and engineers. Remote roles in this field require strong skills in both biology and computer science, as well as the ability to work independently and communicate effectively with remote teams.

What are the key skills and qualifications needed to thrive as a remote machine learning biology professional?

To thrive as a Remote Machine Learning Biology professional, you need a strong foundation in computational biology, machine learning algorithms, programming (such as Python or R), and a relevant degree in bioinformatics, computer science, or biology. Familiarity with bioinformatics tools, data analysis platforms, cloud computing resources, and frameworks like TensorFlow or PyTorch is typically required. Excellent problem-solving, collaboration, and communication skills are essential for effectively interpreting results and working with interdisciplinary teams in a remote environment. These skills and qualities are crucial for advancing biological research through data-driven insights and ensuring effective teamwork and project delivery in a virtual setting.

How do remote machine learning biology professionals typically collaborate with experimental biologists and other team members?

Remote machine learning biology professionals often work closely with experimental biologists, bioinformaticians, and data engineers through virtual meetings, shared project management tools, and collaborative coding platforms. Regular communication is vital to ensure alignment on research objectives, data requirements, and interpretation of results. Team members typically share data, code, and experimental findings using cloud-based repositories, while frequent check-ins help address challenges and maintain project momentum. This collaborative approach allows remote professionals to contribute effectively to interdisciplinary research, despite physical distance.

What is the difference between Remote Machine Learning Biology vs Remote Bioinformatics Specialist?

AspectRemote Machine Learning BiologyRemote Bioinformatics Specialist
Required CredentialsMaster's or PhD in Biology, Data Science, or related fields; experience in machine learningBachelor's or Master's in Bioinformatics, Biology, or Computer Science; programming skills
Work EnvironmentResearch labs, biotech companies, or academic institutions with remote optionsResearch institutions, healthcare, or biotech firms with remote roles
Industry UsageUsed in biotech, pharmaceuticals, and research to analyze biological data with MLApplied in genomics, proteomics, and clinical data analysis

Remote Machine Learning Biology focuses on applying machine learning techniques to biological data, often requiring advanced degrees and programming skills. Remote Bioinformatics Specialists analyze biological datasets using bioinformatics tools. Both roles are vital in biotech and research industries, but they differ in technical focus and required expertise.

What are popular job titles related to Remote Machine Learning Biology jobs in Minnesota?

For Remote Machine Learning Biology jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Biology jobs in Minnesota look for?

The top searched job categories for Remote Machine Learning Biology jobs in Minnesota are:

What cities in Minnesota are hiring for Remote Machine Learning Biology jobs?

Cities in Minnesota with the most Remote Machine Learning Biology job openings:

Remote Machine Learning Biology jobs near you
Infographic showing various Remote Machine Learning Biology job openings in Minnesota as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Saint Cloud, MN • Remote

Full-time

Re-posted 15 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply