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Remote Ai Data Collection Jobs in Michigan (NOW HIRING)

micro1 AI

AI Trainer - Microbiology Expert

Detroit, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Detroit, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Lansing, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Lansing, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Warren, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

micro1 AI

AI Trainer - Microbiology Expert

Warren, MI · Remote

$70 - $90/hr

Remote micro1 is engaging Microbiologists to contribute their scientific expertise to a unique ... Document experimental findings and processes with a focus on clarity for AI training data.

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All JobsAi Data Collection JobsRemote Ai Data Collection JobsRemote Ai Data Collection Jobs in Michigan

Remote Ai Data Collection information

What skills and qualifications are needed for a remote AI data collection specialist?

To thrive as a Remote AI Data Collection Specialist, you need attention to detail, data management skills, and a basic understanding of machine learning concepts, often supported by a degree in computer science or related fields. Familiarity with data annotation tools, spreadsheets, and platforms like Labelbox or Amazon SageMaker is commonly required. Strong communication, time management, and problem-solving skills are important for collaborating remotely and meeting project deadlines. These abilities ensure accurate, efficient data gathering and annotation, which are critical for the quality and reliability of AI model development.

What is remote AI data collection?

Remote AI data collection refers to the process of gathering and labeling data—such as images, audio, text, or video—from various sources using digital tools, often from a remote location. This data is used to train and improve artificial intelligence and machine learning models. People working in this field can perform tasks like annotating images, transcribing audio, or categorizing text, all from their home or another remote setting. The work is essential for creating accurate AI systems and often offers flexible hours. It usually requires basic computer skills and attention to detail.

What remote jobs can I do with AI?

Remote AI data collection jobs involve gathering and labeling data to train machine learning models, often requiring skills in data annotation, understanding of AI tools, and attention to detail. These roles can include image, text, or audio data labeling and are typically performed using specialized platforms or software, offering flexible schedules for qualified candidates.

What is the difference between Remote Ai Data Collection vs Remote Data Annotator?

AspectRemote Ai Data CollectionRemote Data Annotator
Required CredentialsBasic computer skills, training in data collection toolsAttention to detail, familiarity with annotation software
Work EnvironmentRemote, flexible hours, often on mobile or desktopRemote, flexible hours, often on desktop or specialized platforms
Industry UsageAI training data gathering across various sectorsLabeling and annotating data for machine learning models
Common Search IntentJobs involving data collection for AIJobs focused on data labeling and annotation

Remote Ai Data Collection involves gathering raw data for AI training, often requiring basic technical skills. Remote Data Annotator focuses on labeling and annotating data to improve machine learning models. Both roles are remote, but they differ in tasks and skill requirements, serving different stages of AI data preparation.

What are common challenges in a remote AI data collection role, and how can they be managed?

A common challenge in Remote AI Data Collection roles is ensuring data quality and consistency, especially when working independently without direct supervision. It is important to follow detailed guidelines precisely and communicate proactively with project managers or team leads whenever uncertainties arise. Time management and maintaining motivation can also be challenging when working remotely, so setting a structured schedule and leveraging collaboration tools can help. Regular check-ins with the team and staying updated with project requirements are key to overcoming these challenges and delivering reliable results.

How to be a Remote AI Data Collection?

To work as a remote AI data collector, you should have strong attention to detail, good communication skills, and familiarity with data annotation tools or platforms. Many roles require basic computer skills and the ability to follow specific instructions, often with flexible schedules. Gaining experience in data labeling or annotation can improve your chances of securing such positions.

What are the most commonly searched types of Ai Data Collection jobs in Michigan?

The most popular types of Ai Data Collection jobs in Michigan are:

What are popular job titles related to Remote Ai Data Collection jobs in Michigan?

For Remote Ai Data Collection jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Ai Data Collection jobs in Michigan look for?

The top searched job categories for Remote Ai Data Collection jobs in Michigan are:

What cities in Michigan are hiring for Remote Ai Data Collection jobs?

Cities in Michigan with the most Remote Ai Data Collection job openings:

Remote Ai Data Collection jobs near you

Senior Product Manager, Life Sciences Data Products

Beacon Talent

Detroit, MI • On-site, Remote

$152K - $158K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Senior Product Manager, Life Sciences Data Products (Applied AI)

Location: U.S. (Remote-first) with optional hub-based hybrid
Employment: Full-time
Level: Senior IC (high ownership)
Start: ASAP / Flexible

Beacon Talent is leading a confidential search for a venture-backed company building an applied AI + data platform that supports life sciences teams (biopharma, medtech, and research organizations) with secure access to real-world clinical datasets and tooling that accelerates discovery and development while maintaining high standards for privacy, quality, and responsible use.

The Role

As Senior Product Manager, Life Sciences Data Products, you will own the strategy and execution for a portfolio of data-driven products used by life sciences customers to find, access, evaluate, and operationalize complex clinical datasets for R&D and clinical development workflows.

This is a hands-on, high-agency role—ideal for a PM who loves ambiguous problem spaces, can translate market signals into crisp product bets, and can partner deeply with engineering and data teams to ship scalable product capabilities.

What You’ll Own

  • Product vision & roadmap: Define the life sciences product strategy, identify the highest-leverage problems, and translate them into a sequenced roadmap with measurable outcomes.

  • Discovery & validation: Run customer interviews, workflow mapping, and opportunity sizing to determine what to build, what to standardize, and what to avoid as one-off services.

  • Scalable data products: Build repeatable “productized” capabilities that improve dataset usability, governance, search/retrieval, cohort building, and downstream analytics readiness.

  • AI-assisted workflows: Partner with technical teams to design automation that reduces friction in data access and analysis (e.g., metadata enrichment, quality signals, dataset packaging, evaluation tooling).

  • Execution leadership: Write requirements, define success metrics, manage tradeoffs, and drive delivery from concept through launch—iterating based on usage and customer outcomes.

  • Cross-functional alignment: Collaborate closely with go-to-market partners to ensure positioning, packaging, and feedback loops inform the roadmap without turning the product into custom projects.

  • Market awareness: Stay current on life sciences R&D and clinical development trends and incorporate them into differentiation and product choices.

What We’re Looking For

Required

  • 5+ years building data products or platforms for life sciences and/or healthcare customers.

  • Strong product discovery muscle: customer interviews, problem framing, prioritization, and roadmap ownership.

  • Technical fluency across data infrastructure, APIs, pipelines, and working concepts in ML-enabled products (no need to code).

  • Track record partnering with engineering and data teams to deliver complex, high-impact product work.

  • Excellent communication—credible with technical teams and clear with non-technical stakeholders.

  • Comfort operating in a fast-moving environment with evolving inputs and limited process.

Nice to have

  • 0→1 product experience or taking early products to scale in a regulated domain.

  • UX/product design sensibility with strong intuition for end-user workflows.

  • Prior experience in analytics, data science, or experimentation.

  • Familiarity with privacy, governance, and quality frameworks for sensitive datasets.

Why This Role

  • Direct ownership of a high-impact roadmap at the intersection of life sciences + data platforms + applied AI

  • Meaningful influence over what becomes productized vs. service-heavy

  • Close collaboration with technical leadership and high visibility across the company

Compensation

Competitive base + equity + benefits. (Exact range varies by level and location and will be shared during the process.)