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Senior Generative Ai Engineer Jobs in Michigan (NOW HIRING)

... generative AI tools. - Experience building applications, automations, internal tools, scripts ... guidance from senior technical team members. - Strong communication and collaboration skills ...

AI engineer

Dearborn, MI ยท On-site

$89K - $122K/yr

AI engineer Location: Dearborn, MI,48120- 2 days onsite in a week Employment Type: Full-time ... Experience with Generative AI - LLM and building frontend with React / Chainlit / Streamlit.

Role:: AI Engineer/ Developer Location: Okemos, MI (onsite/ Hybrid) Duration: 12 months+ Rate ... Rapidly prototype applications that demonstrate new capabilities in LLMs or generative AI

Based in Sydney with hybrid flexibility, you'll work at the forefront of generative AI, building ... As a senior member of our AI engineering team, you'll provide technical leadership, mentor ...

The Applied AI Engineer turns ideas into production-ready AI solutionsspanning feasibility, data ... Build and productionize machine learning and generative AI solutions that address prioritized ...

Applied AI Engineer

Detroit, MI

$113K - $136K/yr

Job Summary:The Applied AI Engineer turns ideas into production-ready AI solutions spanning ... generative AI solutions that address prioritized business use casesCreate APIs, services, and ...

The Applied AI Engineer turns ideas into production-ready AI solutions spanning feasibility, data ... Build and productionize machine learning and generative AI solutions that address prioritized ...

Showing results 21-40

Senior Generative Ai Engineer information

What is the difference between Senior Generative Ai Engineer vs Machine Learning Engineer?

AspectSenior Generative Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with generative modelsBachelor's/Master's in CS, Data Science, or related; strong ML fundamentals
Work EnvironmentResearch and development focused, often in AI startups or tech companiesData analysis, model development, often across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech, finance, healthcare, and other sectors utilizing ML solutions

The main difference is that Senior Generative Ai Engineers specialize in developing and optimizing generative models like GPT or GANs, focusing on AI creativity and content generation. Machine Learning Engineers have a broader scope, working on various ML algorithms and applications across multiple industries. Both roles require strong technical skills, but the Senior Generative Ai Engineer's expertise is more specialized in generative AI technologies.

What does a senior generative AI engineer do?

A Senior Generative AI Engineer designs, develops, and implements advanced artificial intelligence models, particularly those focused on generating content such as text, images, or audio. They work with large datasets, build and fine-tune generative models like GPT or diffusion models, and oversee the deployment of these systems into production environments. Additionally, they collaborate with cross-functional teams to integrate AI capabilities into products, optimize model performance, and ensure ethical AI practices are followed.

What are some of the unique challenges senior generative AI engineers face when deploying models in production environments?

Senior Generative AI Engineers often encounter challenges such as ensuring model reliability, addressing biases in generated outputs, and managing the significant computational resources required for deployment. There's also a strong need to collaborate with cross-functional teams, including data engineers, product managers, and domain experts, to ensure the solutions align with business goals and maintain user trust. Balancing innovation with ethical considerations and scalability is crucial in this fast-evolving field.

What are the key skills and qualifications needed to thrive as a senior generative AI engineer, and why are they important?

To thrive as a Senior Generative AI Engineer, you need deep expertise in machine learning, deep learning, and natural language processing, typically backed by an advanced degree in computer science or related fields. Proficiency in frameworks like TensorFlow or PyTorch, experience with cloud platforms (e.g., AWS, Azure), and familiarity with large language models are essential, along with relevant certifications. Strong problem-solving skills, creativity, and effective communication set standout engineers apart in this role. These skills and qualities are crucial for designing innovative AI solutions, collaborating across teams, and advancing the capabilities of generative models in real-world applications.
What are the most commonly searched types of Generative Ai Engineer jobs in Michigan? The most popular types of Generative Ai Engineer jobs in Michigan are:
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What cities in Michigan are hiring for Senior Generative Ai Engineer jobs? Cities in Michigan with the most Senior Generative Ai Engineer job openings:
Infographic showing various Senior Generative Ai Engineer job openings in Michigan as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution.

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Warren, MI โ€ข Remote

Full-time

Re-posted 17 days ago


Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

โ€‹

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelorโ€™s or Masterโ€™s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.