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Remote Ai Data Collection Jobs in Detroit, MI (NOW HIRING)

... data science teams and is open to fully remote candidates, with periodic travel expected for ... Lead the design and build of Utilidata's AI inference platform -- establishing architecture ...

Remote Job Summary: We are seeking seasoned in-house transactional attorneys for a part-time role ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote Job Summary: We are seeking seasoned in-house transactional attorneys for a part-time role ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote Job Summary: We are seeking seasoned in-house transactional attorneys for a part-time role ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote Job Summary: We are seeking seasoned in-house transactional attorneys for a part-time role ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote Job Summary: We are seeking seasoned in-house transactional attorneys for a part-time role ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

Remote We are seeking seasoned M&A attorneys for a part-time role at the forefront of legal AI ... Collaborate with product and research teams to refine data, guidelines, and best practices for AI ...

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Remote Ai Data Collection information

See Detroit, MI salary details

$15

$25

$31

How much do remote ai data collection jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for remote ai data collection in Detroit, MI is $25.05, according to ZipRecruiter salary data. Most workers in this role earn between $23.08 and $25.72 per hour, depending on experience, location, and employer.

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 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 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.

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 the most commonly searched types of Ai Data Collection jobs in Detroit, MI?

The most popular types of Ai Data Collection jobs in Detroit, MI are:

What job categories do people searching Remote Ai Data Collection jobs in Detroit, MI look for?

The top searched job categories for Remote Ai Data Collection jobs in Detroit, MI are:

What cities near Detroit, MI are hiring for Remote Ai Data Collection jobs?

Cities near Detroit, MI with the most Remote Ai Data Collection job openings:

AI Infrastructure Engineer

Ann Arbor, MI • Remote

Utilidata
Utilities • 11 - 50 employees

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 14 days ago


Job description

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically orchestrate power and unlock more compute capacity from existing energy infrastructure. For over a decade, we have applied AI to the electric grid — bringing real-time visibility and power-flow control to complex energy infrastructure. Our Karman platform, built on a custom NVIDIA module, brings that same capability to AI data centers, giving operators a way to better use the power already available to them.
The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end infrastructure that serves Utilidata's AI and ML models across edge deployments, cloud environments, and data center integrations. They are also responsible for designing, building, and owning the integration of power data with AI inference software.  This is Utilidata's first dedicated role of this kind, and will serve as the foundational function for how the company deploys and operates AI capabilities in production. The role requires deep technical expertise in ML model serving, distributed systems, and GPU infrastructure, with a strong emphasis on reliability, performance, and scalability. This position works cross-functionally with product, engineering, and data science teams and is open to fully remote candidates, with periodic travel expected for company retreats and key on-site engagements.
Responsibilities
  • Lead the design and build of Utilidata's AI inference platform — establishing architecture patterns, deployment standards, and operational practices that will scale with the company
  • Own end-to-end model serving infrastructure for Utilidata's AI infrastructure (on-prem and datacenter) 
  • Build and maintain fault-tolerant, high-performance systems for serving AI models at scale, with a focus on low latency, reliability, and cost efficiency
  • Collaborate closely with algorithms engineers to integrate AI inference data and configuration with power optimization algorithms 
  • Optimize GPU utilization and inference performance across our hardware fleet, including NVIDIA accelerators central to Utilidata's edge AI platform
  • Establish MLOps best practices including CI/CD pipelines for model deployment, monitoring, and rollback across environments
  • Contribute to infrastructure roadmap decisions, including build vs. buy tradeoffs, tooling selection, and platform evolution as the team grows

Minimum Qualifications 
  • 5+ years of software engineering experience with a strong focus on AI infrastructure, backend systems, or distributed systems
  • Hands-on experience with AI model serving frameworks (e.g., vLLM, SGLang, Triton, TensorRT, TorchServe, or similar)
  • Understanding of container orchestration and cluster management (Kubernetes, Docker)
  • Experience deploying and operating infrastructure across both datacenter and on-prem environments
  • Strong knowledge of GPU workloads and the tradeoffs that come with them — you understand how inference differs from training, and why it matters
  • Proficiency in Python; C++, CUDA, Go, Rust a plus
  • Excellent communication skills and comfort working cross-functionally in a lean, fast-moving environment
  • Willingness to travel up to 10% of time 

Enhanced Qualifications (Nice to Have) 
  • Dynamo experience a plus
  • Experience with edge AI deployments or constrained compute environments
  • Familiarity with infrastructure as code (Terraform, Helm)
  • Experience with observability platforms (Datadog, Prometheus, Grafana)
  • Background in energy, utilities, or industrial IoT
  • Contributions to open-source ML infrastructure projects

Salary Range: $170,000 to $210,000 base compensation depending on experience plus stock options. Salary will be commensurate with an individual's skills, training, years of experience, and in line with internal compensation bands.
Location: This position can be performed remotely from anywhere in the United States. 
Our Commitments:
Utilidata values the diversity of our team. We provide equal employment opportunities without regard to race, color, religion, creed, sex, gender, sexual orientation, gender identity or expression, national origin, age, physical disability, mental disability, medical condition, pregnancy or childbirth, sexual orientation, genetics, genetic information, marital status, or status as a covered veteran or any other basis protected by applicable federal, state and local laws.
We are committed to:
  • Creating a diverse and inclusive workplace that is welcoming, supportive, affirming and respectful
  • Empowering employees to solve problems and work together to make a difference
  • Providing mentorship and growth opportunities as part of a collaborative team
  • A flexible work environment with flexible paid time off
  • Competitive compensation and benefits, including health, dental, vision, and employer-match 401k

 

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