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Ml Inference Jobs in Michigan (NOW HIRING)

Senior Autonomy Engineer

Ann Arbor, MI

$102K - $140K/yr

... inference/runtime performance work. * Familiarity with heuristic / classical perception, computer vision, multi-target tracking, or sensor fusion concepts. * Familiarity with ML/DL frameworks (e.g ...

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AI Infrastructure Engineer

Ann Arbor, MI · On-site +1

$170K - $210K/yr

... 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 ...

Hands-on experience with major ML frameworks and inference runtimes. * Practical experience with model compression techniques and the associated accuracy/performance trade-offs. * Working knowledge ...

Hands-on experience with major ML frameworks and inference runtimes. * Practical experience with model compression techniques and the associated accuracy/performance trade-offs. * Working knowledge ...

Senior Autonomy Engineer

Ann Arbor, MI · On-site

$102K - $140K/yr

... inference/runtime performance work. * Familiarity with heuristic / classical perception, computer vision, multi-target tracking, or sensor fusion concepts. * Familiarity with ML/DL frameworks (e.g ...

Senior Autonomy Engineer

Ann Arbor, MI · On-site

$102K - $140K/yr

... or to inference/runtime performance work. • Familiarity with heuristic / classical perception, computer vision, multi-target tracking, or sensor fusion concepts. • Familiarity with ML/DL ...

Familiarity with personalization, human behavior modeling, or driver intent inference. * Experience integrating ML systems into production hardware or multi-agent simulation. This role is a full-time ...

Build, fine-tune, and operationalize AI/ML models to support integration scenarios such as: * EDI document classification * Automated mapping suggestions * Schema inference * Exception detection and ...

Apply Early

Google AI Lead Architect

Detroit, MI

$54.75 - $75/hr

Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...

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Ml Inference information

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.

Which 3 jobs will survive AI?

Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.

What are some common challenges faced by ML Inference Engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.

What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Michigan? For Ml Inference jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Michigan look for? The top searched job categories for Ml Inference jobs in Michigan are:
What cities in Michigan are hiring for Ml Inference jobs? Cities in Michigan with the most Ml Inference job openings:
Full Lifecycle AI/ML Engineering Lead

Full Lifecycle AI/ML Engineering Lead

Ford Motor Company

Redford, MI • On-site

$92K - $122K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 18 days ago


Job description

About the Organization

We are undergoing a historic industrial shift-moving from building great vehicles to building the sophisticated, scalable systems that power them. The Advanced Industrial Technology organization was created to operationalize this shift. Our mission is not to deploy isolated tools; it is to build an ecosystem that learns from factory data, transforms it into scalable platforms, and delivers measurable enterprise value.

This organization is designed to position us as a leader in industrial innovation. We accelerate digital evolution and manufacturing excellence by integrating cutting-edge technology directly into our global operations. Our structure includes vertical business units focused on specific technology stacks, supported by shared services that ensure scale and operational consistency.

As part of this team, the Sight Vertical is responsible for building an end-to-end business around AI/ML anomaly detection products using both image data (Sight) and parametric data (Sense). This vertical transforms raw data into actionable manufacturing intelligence through products focused on visual error-proofing, defect detection, and assembly process monitoring.

The Opportunity

Are you a technical leader who thrives at the intersection of software engineering, data science, and physical manufacturing? As the Software Engineering Manager for the Sight Vertical, you will lead a high-performing team of software and data engineers building our computer vision and analytics suite.

While technical mastery in software development is important, your primary mission is leadership. You will be responsible for fostering a culture of engineering excellence, creativity, mentoring talent, and ensuring the seamless delivery of complex software products. You won't just oversee code; you will architect the engineering culture that allows AI models to move from research to global industrial scale.

Minimum Requirements

  • Bachelor's degree in Computer Science, AI/ML, or a related technical field.
  • Leadership Experience: 3+ years of experience directly managing software engineering teams, with a proven track record of hiring, mentoring, and retaining talent.
  • Technical Background: 5+ years of experience in software engineering, specifically involving AI/ML, Computer Vision, or complex data-driven products.
  • Systems Knowledge: Deep understanding of the machine learning lifecycle (data engineering, model training, inference, and monitoring).
  • Agile Proficiency: Extensive experience leading teams in Agile environments, managing sprints, and optimizing delivery velocity.

Preferred Requirements

  • Master's in a technical field related to Computer Vision, Software Development, or Data Science.
  • Experience with MLOps platforms and cloud infrastructure (GCP, Azure, or AWS).
  • Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an industrial or IoT context.
  • Knowledge of industrial communication protocols and edge computing hardware.

Success in the Role

  • Team Health: High team engagement, low turnover, and a clear pipeline for internal career growth.
  • Deployment Velocity: Significant reduction in the time required to move a vision model from development to global production.
  • Engineering Quality: High reliability of deployed systems with minimal site-specific custom engineering required.
  • Business Impact: Measurable improvements in defect detection rates and quality metrics across global manufacturing sites.
  • Technical Standard: Establishing the Sight and Sense products as the gold standard for vision-based anomaly detection within the enterprise.
You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
 
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service 
A generous schedule of paid holidays, including the week between Christmas and New Year's Day 
Paid time off and the option to purchase additional vacation time. 
 
This position is leadership level 6 and ranges from $129,600-244,680. 
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
 
For more information on salary and benefits, click here: https://fordcareers.co/LL6
Visa sponsorship is not available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
 
#LI-Onsite
  #LI-DS2 
 

The Position

Reporting to the Sight Vertical Lead, the Software Engineering Manager is responsible for the execution and technical health of the Sight and Sense product lines. You will lead the engineering team in translating strategic goals into robust, scalable software, ensuring our products meet rigorous industrial standards for global rollout.

Note: This role is 100% on site in the Dearborn, MI area and may require some travel to manufacturing facilities for product development and deployment validation.

What You'll Be Able to Do

  • Engineering Leadership & Mentorship: Lead, coach, and grow a multi-disciplinary team of software and data engineers. Foster a collaborative environment focused on continuous improvement and professional development.
  • Technical Delivery: Own the software development lifecycle for Sight and Sense products. Ensure the team delivers high-quality, maintainable code that meets project milestones and performance benchmarks and results in a reliable and highly scalable product.
  • Architecture & Strategy: Provide technical oversight for software and hardware architecture, MLOps pipelines, technology stack selection, and controls integration. Balance the need for rapid innovation with the stability required for 24/7 manufacturing environments.
  • Cross-Functional Collaboration: Partner closely with Product Managers and stakeholders to translate manufacturing challenges into technical roadmaps and executable engineering backlogs.
  • Platform Integration: Ensure all vision products are built for seamless integration with centralized data and operating platforms, adhering to a "build once, scale everywhere" philosophy.
  • Operational Excellence: Drive engineering best practices, including automated testing, CI/CD, and robust monitoring for models deployed at the "edge" (on-site factory hardware).
  • Innovation:  Drive innovation by integrating Agentic workflows and AI-assisted engineering tools to maximize team productivity and software quality
  • Deployment Oversight: Work with site-level stakeholders to ensure technical solutions account for real-world variables such as factory lighting, line speeds, and network constraints.

Ford logo

About Ford

Sourced by ZipRecruiter

At Ford Motor Company, we believe freedom of movement drives human progress. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career and help us define tomorrow's transportation.

Industry

Civil engineering construction

Company size

51 - 200 Employees

Headquarters location

Doral, FL, US

Year founded

1982