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Machine Learning Defense Jobs in Michigan (NOW HIRING)

Lthc

Principal AI Security Engineer

Dewitt, MI · Hybrid

Designs and implement secure machine learning operations (MLOps) controls for datasets, features ... Leads defensive security and blue team capabilities for AI platforms, including telemetry design ...

Lthc

Principal AI Security Engineer

Dewitt, MI · Hybrid

Designs and implement secure machine learning operations (MLOps) controls for datasets, features ... Leads defensive security and blue team capabilities for AI platforms, including telemetry design ...

Integral

Web Designer Senior

Detroit, MI · On-site

... machine learning, and cloud-native solutions, ensuring compatibility with existing systems. • ... defense, intelligence, and civilian leaders to tackle their most important challenges and deliver ...

Integral

Web Designer Senior

Detroit, MI · On-site

... machine learning, and cloud-native solutions, ensuring compatibility with existing systems. · ... defense, intelligence, and civilian leaders to tackle their most important challenges and deliver ...

Hayward Tyler

Project Estimator

Rochester Hills, MI · On-site

Navy and other defense programs. The Project Estimator will analyze technical drawings ... This position requires an individual with initiative, an interest in learning, and a flexible ...

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Machine Learning Defense information

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in deep learning, data science, and software engineering. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses as part of compensation packages.

How much does Lockheed Martin pay AI?

As a Machine Learning Defense professional at Lockheed Martin, salaries typically range from $80,000 to over $130,000 annually, depending on experience, education, and specific role. Compensation may also include benefits such as health insurance, retirement plans, and performance bonuses, with opportunities for career advancement in defense and aerospace sectors.

What are the key skills and qualifications needed to thrive as a Machine Learning Defense professional, and why are they important?

To thrive as a Machine Learning Defense professional, you need a strong background in computer science, cybersecurity, and machine learning, often supported by degrees in these fields or related certifications. Familiarity with frameworks like TensorFlow or PyTorch, experience with adversarial machine learning techniques, and knowledge of security protocols are typically required. Critical thinking, problem-solving, and strong communication skills are essential for anticipating threats and collaborating with interdisciplinary teams. These skills ensure that AI systems remain robust and secure against evolving cyber threats, protecting sensitive data and organizational integrity.

What jobs pay $2000 a day?

In the field of Machine Learning Defense, highly specialized roles such as senior machine learning engineers, AI security consultants, or cybersecurity analysts working on AI systems can command daily rates of around $2000 or more, especially with extensive experience, advanced certifications, and working on critical projects. These positions often require expertise in AI algorithms, cybersecurity, and relevant tools like Python, TensorFlow, or cybersecurity frameworks, and may involve consulting or contract work with flexible schedules.

What is machine learning defense?

Machine learning defense refers to techniques and strategies designed to protect machine learning models from various security threats, such as adversarial attacks, data poisoning, and model theft. These defenses can include methods like adversarial training, input sanitization, and robust model architectures. The goal is to ensure that machine learning systems remain accurate, reliable, and safe even when faced with malicious attempts to manipulate or exploit them. As machine learning becomes more widely adopted, the importance of effective defenses continues to grow.

Which 3 jobs will survive AI?

In the field of Machine Learning Defense, roles such as cybersecurity analysts, AI security specialists, and data scientists are likely to persist as they require complex judgment, domain expertise, and ongoing adaptation to evolving threats. These jobs involve critical thinking, understanding of adversarial AI techniques, and specialized skills that are difficult to fully automate. Continuous learning and certifications in cybersecurity or AI are valuable for staying relevant in these roles.

What are some common challenges faced by professionals in Machine Learning Defense roles, and how can they be addressed?

Professionals in Machine Learning Defense often encounter challenges such as staying ahead of adversarial attacks, managing model robustness, and keeping up with rapidly evolving threat landscapes. Addressing these challenges typically requires continuous learning, collaboration with cybersecurity and data science teams, and implementing rigorous testing and monitoring frameworks for deployed models. Proactively participating in industry forums and staying updated on the latest research also help in identifying emerging threats and mitigation strategies.
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What cities in Michigan are hiring for Machine Learning Defense jobs? Cities in Michigan with the most Machine Learning Defense job openings:
Machine Learning Defense jobs near you
Senior, ML Engineer - Offline Perception

Senior, ML Engineer - Offline Perception

Torc Robotics

Ann Arbor, MI • On-site

$102K - $140K/yr

Full-time

Posted 28 days ago

Job description

Job Summary:
Torc Robotics is a leader in autonomous driving technology, focused on developing software for automated trucks. The Senior ML Engineer - Offline Perception will design and implement object detection and tracking modules, guide project execution, and enhance data processing capabilities to support analytics models.
Responsibilities:
• Design, implement, test and deploy offline object detection, tracking and fusion modules to automatically create annotations on Cloud Services from logged sensor data (Cameras, Lidars, Radars)
• Demonstrated project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution.
• Stay up to date with the latest developments in AI and ML for autonomous driving.
• Independently develop offline perception models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining
• Documentation of created applications.
• Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows.
• Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation.
• Measure and track auto labeling quality to meet internal customer requirements.
• Guide and produce information products, supporting visualization and data accessibility in a customer-centric manner.
• Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety.
• Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes.
• Provides technical guidance or business process expertise, technical leadership, coaching and mentoring to team members.
Qualifications:
Required:
• Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 6+ years of experience OR;
• Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 3+ years of experience OR;
• Doctorate Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 1+ years of experience.
• Active Learning & Pseudo-labeling - Computer Vision, Deep Learning, Model training.
• Two of the following: 2D/3D Object Detection, Tracking, Sensor Fusion, Semantic Segmentation, SLAM, BEV.
• Scaled ML Operations (MLOps) and Tooling – ML Frameworks, experiment tracking, model registry, MLFLow, Weights and Biases, ML Metrics and Evaluation / Quality.
• Distributed machine learning frameworks - PyTorch, Lightning, Ray.
• Model Data Curation - Parquet data processing (PyArrow, Daft, Pandas, etc).
• Development Tools & Eco-System (at scale) - Proficiency in Python software development. Also, VDI and cloud-based development environments, CI Systems (GitHub Actions), and Docker.
• Knowledge of English is required since the selected candidate will need to collaborate daily with English-speaking colleagues in the United States and work with technical documentation written exclusively in English.
Preferred:
• Data operations and management at scale - Schema design, AWS storage and processing infra, vector databases / LanceDB, file formats (MCAP, parquet, etc).
• Data Visualization - Integration with tooling such as OpenGL, 3.js, foxglove, 51, tableau.
• Cloud Development – Python (proficient level), Terraform, AWS Managed Services (eg S3, ECS, Lambda, Dynamo, Step Functions, Athena).
• Cloud-based orchestration and resource management - AWS Hyperpods, Anyscale, Etc. Model Inference Orchestration.
Company:
Torc provides L4 end-to-end self-driving software for mobility, trucking, mining, and defense markets through strategic partnerships Founded in 2005, the company is headquartered in Blacksburg, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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