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Ai For Science Jobs in Michigan (NOW HIRING)

Join the Foundational Modeling team at Splunk, where we advance the state of AI for highvolume ... Collaborate with engineering, product, and data science teams to understand requirements ...

$50/hr

Sony AI is Sony's new research organization pursuing the mission to use AI to unleash human ... You will receive support from internal scientists and engineers in your efforts. Required ...

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Ai For Science information

What is AI for Science?

AI for Science refers to the application of artificial intelligence and machine learning techniques to accelerate scientific discovery and research. By leveraging large datasets, complex models, and advanced computational methods, AI helps scientists analyze data, identify patterns, simulate experiments, and make predictions across various scientific fields such as biology, chemistry, physics, and climate science. This approach can significantly speed up research, uncover new insights, and solve problems that were previously too complex or time-consuming for traditional methods.

How does collaboration typically work between AI for Science professionals and domain experts in research teams?

AI for Science professionals frequently work closely with experts in fields such as biology, chemistry, or physics to identify scientific problems that can benefit from machine learning techniques. Collaboration usually involves regular meetings to translate complex scientific challenges into data-driven models, sharing domain knowledge, and iteratively refining solutions. Effective communication and a willingness to bridge gaps between computational and scientific perspectives are essential. This interdisciplinary teamwork not only enhances the impact of AI solutions but also fosters ongoing learning and innovation.

What are the key skills and qualifications needed to thrive as an AI for Science specialist, and why are they important?

To thrive as an AI for Science Specialist, you need a strong background in computer science, mathematics, and scientific domains, often supported by advanced degrees (e.g., PhD or MSc) in relevant fields. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools, and familiarity with high-performance computing environments are typically required. Critical thinking, interdisciplinary collaboration, and effective communication are crucial soft skills for translating scientific problems into AI solutions. These skills are vital for developing innovative models, ensuring research rigor, and enabling impactful scientific discoveries.

What is the difference between Ai For Science vs Data Scientist?

AspectAi For ScienceData Scientist
Required CredentialsDegree in Science, Computer Science, or related fields; knowledge of AI and machine learningDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentResearch labs, scientific institutions, tech companies focused on scientific applicationsCorporate, tech firms, finance, healthcare, and other industries analyzing data
Industry UsageApplied to scientific research, simulations, and experimental data analysisUsed for data analysis, predictive modeling, and business insights

Ai For Science focuses on applying AI techniques to scientific research and experiments, often requiring a background in science and specialized knowledge of AI. Data Scientists analyze large datasets across various industries to extract insights and build models. While both roles involve AI and data analysis, Ai For Science is more research-oriented within scientific contexts, whereas Data Scientists work across diverse sectors on data-driven decision making.

What job categories do people searching Ai For Science jobs in Michigan look for?

The top searched job categories for Ai For Science jobs in Michigan are:

What cities in Michigan are hiring for Ai For Science jobs?

Cities in Michigan with the most Ai For Science job openings:

Infographic showing various Ai For Science job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 21% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution.

Staff Software Engineer, AI for Developer Productivity

General Motors

Warren, MI • On-site

$160.20 - $246.30/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 27 days ago


General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 306 frontline employees who took The Breakroom Quiz

7.4

Company rating compared to similar companies: 7.4 out of 10

Automakers average

Based on 6,288 frontline employees who took The Breakroom Quiz


Job description

Staff Software Engineer, AI for Developer Productivity page is loaded## Staff Software Engineer, AI for Developer ProductivityApplyremote type: Hybridlocations: Warren, Michigan, United States of America: Mountain View Technical Center - Mountain View Technical Center: Austin, Texas, United States of Americatime type: Full timeposted on: Posted Todayjob requisition id: JR-202612378**Job Description**We are seeking a highly skilled Staff Software Engineer to join the Virtualization & Embedded Software Development Tools organization.In this role, you will apply artificial intelligence to improve developer productivity, modernize engineering workflows, and advance toolchain capabilities across embedded software development. You will shape and deliver practical, production-grade AI capabilities that help engineers build, test, analyze, troubleshoot, and support complex software systems more effectively at scale.This role is ideal for a recognized technical expert who thrives in ambiguity, works independently with broad latitude, influences key technical decisions, and leads large cross-functional efforts with broad visibility. You will partner across CI/CD, virtualization, systems engineering, calibration, platform, and software development teams to identify high-value opportunities and turn them into scalable solutions that improve engineering throughput, reliability, and user experience.Our organization supports the end-to-end engineering toolchain that enables teams to define, develop, validate, calibrate, and release embedded software and systems. That includes engineering tools, build and test workflows, dashboards, automation, integrations, and engineering support platforms. As part of this team, you will help define how AI can be used responsibly and effectively in real engineering environments to improve speed, quality, and user experience.**What you’ll do*** Define the technical vision for AI-powered developer productivity capabilities across engineering tools and workflows* Design, develop, and deliver AI-powered solutions that reduce manual effort, accelerate issue resolution, and improve software quality across development, debugging, test analysis, issue triage, documentation, and engineering support workflows* Partner with cross-functional teams to identify high-value AI use cases and translate them into scalable products, platforms, and reusable capabilities* Integrate AI-powered capabilities into engineering tools, workflows, and automation platforms in ways that improve reliability, usability, and adoption* Lead architecture and implementation decisions for AI systems spanning model access, orchestration, retrieval, evaluation, observability, security, and enterprise integration* Drive productionization of AI capabilities within GM engineering environments, including cloud-hosted services, internal platforms, CI/CD systems, and developer tools* Establish technical standards and best practices for responsible use of AI in engineering tools, including quality, traceability, maintainability, and cybersecurity considerations* Serve as a subject matter expert and technical leader across organizational boundaries, influencing roadmaps, solution direction, and implementation priorities* Mentor engineers on AI system design, prompt and workflow design, evaluation strategies, and toolchain integration without formal people-leader responsibility* Present strategy, progress, recommendations, and demonstrations to technical leaders and partner organizations**Additional job description****Your skills and abilities (required qualifications)*** Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or a related technical field* 10+ years of experience in software engineering, developer tooling, platform engineering, machine learning engineering, applied AI, or a closely related field* Strong expertise building and shipping production software systems, with proficiency in Python and at least one additional language used in engineering tooling environments* Demonstrated expertise applying AI and LLM-based approaches to engineering problems such as code analysis, workflow automation, knowledge retrieval, summarization, troubleshooting, or developer productivity support* Strong understanding of software engineering fundamentals, system design, APIs, data flows, observability, and production operations* Experience integrating AI-powered capabilities into enterprise platforms, engineering tools, or CI/CD systems* Experience with cloud services, containerization, and orchestration technologies* Strong knowledge of secure engineering practices and responsible AI guardrails* Demonstrated success leading technically ambiguous, cross-functional efforts from concept through production deployment* Excellent communication skills and the ability to influence technical direction across teams without formal authority* Experience with developer platforms, build systems, testing systems, or internal engineering tools* Experience balancing fast experimentation with production reliability, maintainability, and compliance**What can give you a competitive edge (preferred qualifications)*** Master’s degree or PhD in Computer Science, Software Engineering, Machine Learning, AI, or a related field* Experience in embedded software development, automotive software, systems engineering, or safety-related toolchains* Experience with CI/CD platforms, build and test orchestration, and software quality automation* Familiarity with GM engineering tools, engineering workflows, or internal platform environments* Experience building AI assistants, coding agents, or domain-specific AI capabilities for engineers* Experience with knowledge systems, vector search, ranking, workflow orchestration, or code intelligence platforms* Experience supporting large engineering communities through reusable tools, templates, and automation* Experience evaluating AI quality in production systems using measurable outcomes such as acceptance rate, time saved, precision and recall, hallucination reduction, or workflow completion rate* Experience designing retrieval-augmented or tool-using AI workflows* Experience integrating AI into GitHub-based engineering workflows or related enterprise automation pipelines**Why join us**This is an opportunity to shape how AI is applied in real-world engineering environments at scale. You will work on high-value problems at the intersection of developer productivity, toolchain modernization, automation, CI/CD, observability, and embedded software development. Your work will help engineering teams move faster, reduce friction, improve quality, and unlock new capabilities across a critical part of GM’s software development ecosystem.You will join a team that is actively modernizing and scaling core engineering toolchains, including CI/CD robustness, workflow automation, dashboarding and observability, configuration and calibration workflows, and platform evolution. This role offers the opportunity to turn promising AI concepts into reliable, enterprise-ready capabilities that deliver measurable value.*Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position, as well as geography of the selected candidate. • The salary range for this role is ($160,200 - 246,300). The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position. • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance. Benefits: • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.**#LI-JK3*GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc).This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.This job is not eligible for relocation benefits. Any relocation costs would be the responsibility of the selected candidate. #J-18808-Ljbffr

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About General Motors

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General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908