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

Utilidata

Principal Data Engineer

Ann Arbor, MI · Remote

$170K - $210K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... We're looking for a Principal Data Engineer to own the technical direction and execution of our ...

company826

AI/ML and Data Engineer

Southfield, MI · On-site +1

$104K - $125K/yr

Bachelor's degree required in Computer Science, Engineering, Data Science, or related field; advanced degree preferred. * At least 8 years of progressive experience in AI/ML engineering, including a ...

Utilidata

AI Infrastructure Engineer

Ann Arbor, MI · Remote

$170K - $210K/yr

The AI Infrastructure Engineer is responsible for designing, building, and owning the end-to-end ... data science teams and is open to fully remote candidates, with periodic travel expected for ...

Protera Health

Senior Data Engineer

Troy, MI · On-site +1

$100K - $136K/yr

You will champion the safe AI principles fundamental to our engineering culture. Key ... Fully remote work: work from your home or other private, secured area to help fit your lifestyle

Utilidata

Senior Software Engineer, DevOps

Ann Arbor, MI · Remote

$160K - $190K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

Utilidata

Senior Software Engineer, DevOps

Ann Arbor, MI · On-site +1

$160K - $190K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

Utilidata

VP, AI & Applications

Ann Arbor, MI · Remote

$230K - $290K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... The VP partners with the VP, Engineering on the platform that runs these methods in production, and ...

Utilidata

Software Engineer, On Device

Ann Arbor, MI · On-site +1

$120K - $150K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

Utilidata

Software Engineer, On Device

Ann Arbor, MI · Remote

$120K - $150K/yr

Utilidata is a fast-growing NVIDIA-backed AI company enabling AI data centers to dynamically ... remote work. Our Commitments: Utilidata values the diversity of our team. We provide equal ...

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All JobsAi Data Engineer JobsRemote Ai Data Engineer JobsRemote Ai Data Engineer Jobs in Detroit, MI

Remote Ai Data Engineer information

See Detroit, MI salary details

$44.1K

$128.4K

$175.7K

How much do remote ai data engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for remote ai data engineer in Detroit, MI is $128,415.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,400.00 and $136,100.00 per year, depending on experience, location, and employer.

What is a remote AI data engineer?

A Remote AI Data Engineer is a professional who designs, builds, and maintains data pipelines and infrastructure to support artificial intelligence (AI) and machine learning (ML) projects, all while working from a remote location. They are responsible for collecting, cleaning, transforming, and storing large datasets, ensuring data quality and accessibility for AI applications. These engineers collaborate with data scientists, software engineers, and stakeholders to deliver data solutions that power intelligent systems, often leveraging cloud technologies and distributed computing. Their work enables organizations to harness data for predictive analytics, automation, and decision-making—without being tied to a physical office.

What are the key skills and qualifications needed to thrive as a remote AI data engineer?

To thrive as a Remote AI Data Engineer, you need strong programming skills (Python, SQL), a solid understanding of data structures, machine learning principles, and typically a degree in computer science or related fields. Familiarity with big data platforms (such as Hadoop or Spark), cloud services (AWS, GCP, or Azure), and experience with AI/ML frameworks like TensorFlow or PyTorch are commonly required. Excellent problem-solving, communication, and self-motivation skills help you collaborate effectively and manage projects independently in a remote setting. These skills and qualities ensure robust AI data pipelines, effective model deployment, and seamless teamwork across distributed environments.

What are some common challenges faced by remote AI data engineers, and how can they be addressed?

Remote AI Data Engineers often encounter challenges such as coordinating with cross-functional teams across different time zones, ensuring data security when accessing sensitive datasets remotely, and maintaining effective communication for project updates. To address these, it's important to establish clear protocols for data sharing, leverage collaboration tools (like Slack or Jira), and schedule regular check-ins to align with team goals. Adopting strong version control practices and automated testing can also help streamline workflows and minimize errors in a distributed environment.

What is the difference between Remote Ai Data Engineer vs Data Scientist?

AspectRemote Ai Data EngineerData Scientist
Required CredentialsBachelor's in CS, Data Engineering, or related; experience with cloud platformsBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentData pipelines, cloud infrastructure, codingData analysis, statistical modeling, visualization
Employer & Industry UsageTech companies, AI firms, startupsResearch institutions, tech companies, finance
Common Search & ComparisonYesYes

Remote Ai Data Engineers focus on building and maintaining data pipelines and infrastructure for AI applications, requiring skills in data engineering and cloud platforms. Data Scientists analyze data, develop models, and generate insights. While both roles work with data, Data Engineers prepare the data environment, whereas Data Scientists interpret and model the data. They often collaborate but serve different functions in AI and data projects.

What are popular job titles related to Remote Ai Data Engineer jobs in Detroit, MI?

For Remote Ai Data Engineer jobs in Detroit, MI, the most frequently searched job titles are:

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

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

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

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

Remote Ai Data Engineer jobs near you

Principal Data Engineer

Utilidata

Ann Arbor, MI • Remote

$170K - $210K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

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.
We're looking for a Principal Data Engineer to own the technical direction and execution of our data engineering platform. This role is responsible for setting architectural direction for the data systems that underpin our products, make critical design decisions about how we collect, process, store, and serve data at scale, and raise the bar for the entire team through your judgment, communication, and hands-on engineering. You'll operate at the intersection of deep technical work and cross-functional leadership, translating product goals into sound engineering plans and guiding the team through ambiguity to deliver real results. You'll own the component-level architecture for the data platform while working in close partnership with the platform architect to ensure alignment with the end-to-end platform vision and architecture. You'll join a diverse team of experts who are mission-driven, collaborative, and adaptive, and guide the team through the challenges of building reliable, performant data infrastructure in a fast-moving environment.
Responsibilities
  • Architect and contribute directly to core platform components, including ingestion pipelines, transformation frameworks, data models, and orchestration
  • Define and evolve the multi-quarter technical roadmap for the data platform, balancing new capabilities, reliability investments, and technical debt reduction in alignment with the broader platform architecture
  • Drive evaluation and adoption of tooling across the stack, ensuring choices are well-reasoned and aligned with where the platform needs to go
  • Lead architecture reviews and design discussions, ensuring decisions are well-reasoned, documented, and understood by the team
  • Cut through ambiguity by asking the right questions early about data quality, schema evolution, and downstream dependencies, and identify risks before they become crises
  • Translate complex data infrastructure decisions for non-technical stakeholders without oversimplifying, and break vague product requirements into clear engineering tasks and acceptance criteria
  • Partner closely with data science leads and cross-functional teams to surface dependencies and constraints early and prioritize improvements that unlock productivity
  • Run a lightweight but effective backlog and planning process, keeping the team focused and unblocked
  • Mentor and grow engineers with an emphasis on raising technical depth — delegate meaningful work, pair on hard problems, and create opportunities for others to stretch
  • Set code review standards, testing philosophy, and engineering best practices that make the whole team better, including data validation, pipeline testing, and schema management
  • Ensure data systems work reliably in production — instrumented, observable, and operable, with clear SLAs on freshness, completeness, and accuracy

Minimum Qualifications
  • At least 8 years of experience in data engineering, with 2+ years operating at a principal or staff level
  • Proven ability to design and evaluate end-to-end data platforms across ingestion, transformation, storage, and serving, with clean contracts between layers
  • Deep understanding of data pipeline design, with fluency in the patterns and tradeoffs of batch and streaming pipelines at scale
  • Strong understanding of data modeling and storage strategies
  • Strong software engineering fundamentals, with the depth to evaluate code quality and set architectural standards
  • Strong experience with cloud data infrastructure (AWS, GCP, or Azure) and the surrounding ecosystem
  • Demonstrated ability to lead technical teams, set direction, and grow engineers without relying on formal authority

Enhanced Qualifications (Nice to Have)
  • Experience with streaming architectures (Spark Structured Streaming, Delta Live Tables, Kafka)
  • Familiarity with data quality and observability tooling (Great Expectations, Monte Carlo, Soda, or similar)
  • Background working with visualization tools connected to Databricks (Databricks Dashboards, Tableau, Sigma, Power BI)
  • Experience with data collection from edge devices
  • Experience supporting ML workflows, including feature engineering pipelines, feature stores, or model input data preparation

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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