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Ai Research Assistant Jobs in Rochester, MI (NOW HIRING)

Team Rehabilitation

Physical Therapist Assistant

Novi, MI · On-site

$26 - $32/hr

Sidekick AI documentation assistant to help reduce charting time. * A strong Equity & Engagement ... Participate in clinic research studies. * Continue to grow professionally through CEUs and approved ...

Team Rehabilitation

Physical Therapist Assistant

Troy, MI · On-site

$26 - $32/hr

Sidekick AI documentation assistant to help reduce charting time. * A strong Equity & Engagement ... Participate in clinic research studies. * Continue to grow professionally through CEUs and approved ...

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All JobsAi Research JobsAi Research Assistant JobsAi Research Assistant Jobs in Rochester, MI

Ai Research Assistant information

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How much do ai research assistant jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for ai research assistant in Rochester, MI is $20.17, according to ZipRecruiter salary data. Most workers in this role earn between $17.02 and $23.46 per hour, depending on experience, location, and employer.

What is an AI Research Assistant?

An AI Research Assistant is a professional who supports artificial intelligence research projects by performing tasks such as data collection, literature reviews, running experiments, and analyzing results. They often work alongside AI researchers and engineers to help develop new algorithms, models, or applications in machine learning and related fields. The role may involve programming, using statistical tools, and staying updated on the latest advancements in AI. AI Research Assistants are commonly found in academic, corporate, or research lab environments. Their work is crucial for advancing the field and supporting innovation in AI.

What are some common challenges faced by AI Research Assistants when working on collaborative projects?

AI Research Assistants often collaborate with multidisciplinary teams, including data scientists, software engineers, and senior researchers. One common challenge is ensuring clear communication of complex technical findings to team members with varying expertise. Balancing multiple projects with competing deadlines can also be demanding, requiring strong organizational skills. Additionally, rapidly evolving research topics may necessitate frequent upskilling and adaptability to new tools and methodologies.

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

To thrive as an AI Research Assistant, you need a solid background in computer science, mathematics, and machine learning, often supported by a relevant degree or coursework. Familiarity with programming languages like Python, machine learning frameworks such as TensorFlow or PyTorch, and experience using data analysis tools are typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with research teams and interpret complex results. These skills are essential for contributing to innovative AI projects, ensuring accurate research outcomes, and supporting the advancement of artificial intelligence.

What is the difference between Ai Research Assistant vs Data Scientist?

AspectAi Research AssistantData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fieldsBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, AI development teams, academic settingsBusiness, tech companies, analytics teams
Industry UsageAI research projects, academic research, R&D departmentsData analysis, predictive modeling, business insights
Common Search IntentUnderstanding AI research roles, entry-level AI research jobsData analysis careers, data-driven decision making

While both roles involve working with data and algorithms, an Ai Research Assistant primarily supports AI research projects, focusing on developing and testing AI models. A Data Scientist, on the other hand, analyzes data to generate insights and inform business decisions. The roles often overlap in skills and credentials but differ in their core focus and work environment.

How much do AI research assistants make?

AI research assistants typically earn between $50,000 and $90,000 annually, depending on experience, education, and location. Entry-level positions may start lower, while those with advanced skills in machine learning and data analysis can earn higher salaries, often with opportunities for growth in research environments or tech companies.

How to become an AI research assistant?

To become an AI research assistant, candidates typically need a strong background in computer science, mathematics, or related fields, often holding a bachelor's or master's degree. Skills in programming languages like Python, experience with machine learning frameworks, and familiarity with research methodologies are essential. Gaining experience through internships, academic projects, or contributing to research papers can improve prospects in this role.

What job categories do people searching Ai Research Assistant jobs in Rochester, MI look for?

The top searched job categories for Ai Research Assistant jobs in Rochester, MI are:

What cities near Rochester, MI are hiring for Ai Research Assistant jobs?

Cities near Rochester, MI with the most Ai Research Assistant job openings:

Ai Research Assistant jobs near you
Infographic showing various Ai Research Assistant job openings in Rochester, MI as of August 2026, with employment types broken down into 79% Full Time, and 21% Part Time. Highlights an 93% In-person, and 7% Remote job distribution, with an average salary of $41,946 per year, or $20.2 per hour.

Principal Engineer - HR AI Solutions

Harman International Industries

Novi, MI • On-site

Full-time

Re-posted 7 days ago

Job description

A Career at HARMAN
As a technology leader that is rapidly on the move, HARMAN is filled with people who are focused on making life better. Innovation, inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together, you'll discover that at HARMAN you can grow, make a difference and be proud of the work you do every day.
Introduction: A Career at HARMAN Automotive
We're a global, multi-disciplinary team that's putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive, we give you the keys to fast-track your career.
  • Engineer audio systems and integrated technology platforms that augment the driving experience
  • Combine ingenuity, in-depth research, and a spirit of collaboration with design and engineering excellence
  • Advance in-vehicle infotainment, safety, efficiency, and enjoyment

About the Role
Drive hands-on delivery of AI and Generative AI solutions for Digital HR and HR Business Partners. You will combine full-stack AI development with strong HR process, data, privacy, and governance awareness to solve business problems across the employee lifecycle, workforce planning, skills intelligence, talent, learning, case management, and employee experience.
This role is not centered on configuring one HR platform. Instead, you will evaluate AI capabilities across tools and vendors, advise HR stakeholders on where AI can create value, and build practical solutions when custom development, orchestration, or integration is the right path. You will architect, develop, and maintain production-grade systems that may include RAG pipelines, agentic workflows, model routing, vector search, evaluation, guardrails, observability, analytics, and visualizations integrated with enterprise HR data products and internal platforms.
What You Will Do
  • Solve HR business problems with AI: Partner with Digital HR, HR COEs, HRIS, IT, Legal, Privacy, and regional stakeholders to understand business needs and identify where AI can automate work, generate insight, or improve decision support.
  • Act as a trusted AI consultant: Advise HR teams on AI opportunities, risks, implementation options, data readiness, governance requirements, and the trade-offs between vendor capabilities, configuration, integration, and custom development.
  • Build AI-enabled HR solutions end to end: Develop prototypes and production solutions such as HR knowledge copilots, employee policy assistants, case triage tools, document summarization, onboarding support, skills intelligence, workforce planning analytics, and AI-assisted process workflows.
  • Evaluate AI tools vendor-neutrally: Assess capabilities across HR and enterprise platforms such as Workday, ServiceNow, Microsoft, and emerging AI tools, focusing on concepts, fit, value, and feasibility rather than deep specialization in one system.
  • Design and implement RAG pipelines: Build retrieval solutions over HR policies, job profiles, skills taxonomies, learning content, business rules, case data, requirements documents, lessons learned, and other structured or unstructured HR content.
  • Develop agentic workflows: Use orchestration frameworks and agent patterns to translate HR processes into reliable AI-enabled workflows with appropriate human review, escalation, and auditability.
  • Create analytics and visualizations: Move beyond static reporting by developing AI-driven insight generation, workforce skill heat maps, automation and augmentation analysis, replacement-impact views, and decision-support tools from integrated HR data products.
  • Implement enterprise-grade controls: Build guardrails, content policies, safety filters, prompt/version management, model evaluation, latency and throughput tuning, cost controls, fallback strategies, and model-routing approaches.
  • Protect HR data: Design solutions with privacy, PII protection, role-based access, employee-data sensitivity, works council considerations, retention requirements, and model/data governance built in from the start.
  • Operate production solutions: Containerize applications, automate CI/CD, monitor usage and quality, debug production issues, manage observability, and improve cost, reliability, and performance over time.
  • Communicate clearly and iterate quickly: Translate complex AI concepts for non-technical HR stakeholders, document recommendations, share demos, gather feedback, and build trust through practical value delivery.

What You Need To Be Successful
  • Experience: 8+ years of experience building production software or data products, including hands-on experience with ML, LLMs, Generative AI, or AI-enabled workflow automation.
  • AI and GenAI foundations: Strong conceptual and practical understanding of LLMs, embeddings, RAG, agentic workflows, prompt engineering, model orchestration, model evaluation, guardrails, and responsible AI practices.
  • Programming: Proficiency with Python, such as FastAPI, NumPy, Pandas, scikit-learn, Pydantic, and Jinja2, plus Node.js or TypeScript; strong experience with APIs, distributed systems, and integration patterns.
  • Full-stack delivery: Ability to build internal applications, dashboards, copilots, and workflow tools using modern front-end and back-end patterns, such as React, REST or GraphQL services, and reusable UI/data components.
  • Data and search: Experience with SQL and NoSQL databases, search and analytics platforms, vector databases such as Pinecone, Weaviate, FAISS, Milvus, or pgvector, and practical knowledge of chunking, reranking, retrieval quality, and data-product design.
  • Model providers and frameworks: Working familiarity with inference providers and model ecosystems such as AWS Bedrock, Azure OpenAI, OpenAI, Anthropic, Meta/Llama, and Mistral, along with orchestration frameworks such as LangChain, LlamaIndex, MCP, or comparable approaches.
  • Cloud and infrastructure: Experience with cloud platforms such as AWS, Azure, or GCP; Docker, Kubernetes, Terraform, CI/CD, observability tools, and production support practices.
  • HR domain awareness: Understanding of HR data, employee lifecycle processes, people analytics, skills and job architecture, talent and learning processes, case management, workforce planning, and the sensitivity of employee information.
  • Governance mindset: Ability to design for privacy, PII protection, role-based access, auditability, human-in-the-loop review, regulatory considerations, works council approvals, and enterprise model/data governance.
  • Consulting and communication: Strong business-problem framing, product-oriented thinking, stakeholder facilitation, clear communication, and the ability to explain AI options to HR leaders and subject-matter experts.
  • Education: BS, MS, or PhD in Computer Science, Data Science, Electrical Engineering, Mathematics, Human Resources Technology, or equivalent professional experience.

Preferred Experience
  • Experience developing AI solutions for HR, people analytics, talent, learning, recruiting, employee experience, HR service delivery, or workforce planning use cases.
  • Familiarity with HR and enterprise AI platforms such as Sana AI, Workday, ServiceNow HRSD, SAP SuccessFactors, or Microsoft 365/Copilot ecosystems; platform-specific configuration experience is helpful but not required.
  • Experience creating skills intelligence, workforce planning, automation-potential analysis, or organizational heat-map visualizations.
  • Experience working with Legal, Privacy, Information Security, Works Councils, or equivalent governance bodies on employee-data solutions.

What Makes You Eligible
  • Ability to work from an office in Novi, MI, 3+ days per week (hybrid)
  • Successfully complete a background investigation and drug screen as a condition of employment.

What We Offer
  • Access to employee discounts on world-class products (JBL, HARMAN Kardon, AKG, and more).
  • Extensive training opportunities through our own HARMAN University.
  • Competitive wellness benefits.
  • Tuition reimbursement.
  • "Be Brilliant" employee recognition and rewards program.
  • An inclusive and diverse work environment that fosters and encourages professional and personal development.

#Hybrid
#LI-AA1
Salary Ranges:
$ 125,250 - $ 183,700
HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

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