The ML Engineer will work on deploying trained Machine Learning Models on embedded hardware ... Responsibilities : • Develop modern C++ and CUDA code for AI inference, including data processing ...
The ML Engineer will work on deploying trained Machine Learning Models on embedded hardware ... Responsibilities : • Develop modern C++ and CUDA code for AI inference, including data processing ...
The ML Engineer in the Acceleration Team will deploy trained Machine Learning Models on embedded ... Responsibilities : • Develop modern C++ and CUDA code for AI inference, including data processing ...
The ML Engineer in the Acceleration Team will deploy trained Machine Learning Models on embedded ... Responsibilities : • Develop modern C++ and CUDA code for AI inference, including data processing ...
... inference and automation workflows Develop reusable integration patterns and data structures to ... ML, data science, or advanced analytics Experience delivering production-grade solutions in ...
... inference and automation workflows Develop reusable integration patterns and data structures to ... ML, data science, or advanced analytics Experience delivering production-grade solutions in ...
Job Title AI/ML Specialist (Data Science & Intelligent Automation) Overview / Summary We are ... Design and maintain data pipelines supporting model inference and automation workflows * Develop ...
Job Title AI/ML Specialist (Data Science & Intelligent Automation) Overview / Summary We are ... Design and maintain data pipelines supporting model inference and automation workflows * Develop ...
Senior, ML Engineer - Offline Perception
Ann Arbor, MI · On-site +1
$102.20K - $140.40K/yr
Stay up to date with the latest developments in AI and ML for autonomous driving. * Independently ... Model Inference Orchestration. Perks of Being a Full-time Torc'r Torc cares about our team members ...
Senior, ML Engineer - Offline Perception
Ann Arbor, MI · On-site +1
$102.20K - $140.40K/yr
Stay up to date with the latest developments in AI and ML for autonomous driving. * Independently ... Model Inference Orchestration. Perks of Being a Full-time Torc'r Torc cares about our team members ...
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Manager, Data Engineering
Birmingham, MI · On-site
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Manager, Data Engineering
Birmingham, MI · On-site
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Manager, Data Engineering
Birmingham, MI · On-site
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Manager, Data Engineering
Birmingham, MI · On-site
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Full Lifecycle AI/ML Engineering Lead
$92.70K - $122K/yr
Deep understanding of the machine learning lifecycle (data engineering, model training, inference ... Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an ...
Full Lifecycle AI/ML Engineering Lead
$92.70K - $122K/yr
Deep understanding of the machine learning lifecycle (data engineering, model training, inference ... Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an ...
Manager, Data Engineering
Birmingham, MI · On-site
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Manager, Data Engineering
Birmingham, MI · On-site
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Create robust data processing workflows for model training and inference MLOps & Infrastructure * Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Full Lifecycle AI/ML Engineering Lead
$92.70K - $122K/yr
Deep understanding of the machine learning lifecycle (data engineering, model training, inference ... Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an ...
Full Lifecycle AI/ML Engineering Lead
$92.70K - $122K/yr
Deep understanding of the machine learning lifecycle (data engineering, model training, inference ... Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an ...
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 ...
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 ...
Full Lifecycle AI/ML Engineering Lead
Redford, MI · On-site
$92.70K - $122K/yr
Deep understanding of the machine learning lifecycle (data engineering, model training, inference ... Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an ...
Full Lifecycle AI/ML Engineering Lead
Redford, MI · On-site
$92.70K - $122K/yr
Deep understanding of the machine learning lifecycle (data engineering, model training, inference ... Experience scaling AI/ML products from a single pilot to a global enterprise footprint in an ...
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 ...
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 ...
AI Engineer Consultant
Detroit, MI · Hybrid
Deliver governed data and features for ML/GenAI (curated datasets, feature pipelines/serving) supporting training and real-time inference, including consistency, caching, backfills, and latency SLOs.
AI Engineer Consultant
Detroit, MI · Hybrid
Deliver governed data and features for ML/GenAI (curated datasets, feature pipelines/serving) supporting training and real-time inference, including consistency, caching, backfills, and latency SLOs.
AI Engineer Consultant
Detroit, MI · Hybrid
Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...
AI Engineer Consultant
Detroit, MI · Hybrid
Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...
AI Engineer III
Detroit, MI · Hybrid
Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...
AI Engineer III
Detroit, MI · Hybrid
Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). A successful candidate would possess ...
AI Data Engineer - Senior Consultant
Midland, MI · Hybrid
$89.70K - $123.10K/yr
Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). * Implement safety, privacy, and ...
AI Data Engineer - Senior Consultant
Midland, MI · Hybrid
$89.70K - $123.10K/yr
Deliver governed datasets and feature engineering/serving for ML training and real-time inference (online/offline consistency, caching, latency SLOs, backfills). * Implement safety, privacy, and ...
Ml Inference information
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 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.
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?
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research 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 are popular job titles related to Ml Inference jobs in Michigan? For Ml Inference jobs in Michigan, the most frequently searched job titles are:
- Preclinical Imaging Scientist
- Computational Scientist
- Remote Pharmaceutical Data Scientist
- Computational Scientist Remote
- Computational Neuroscience Phd
- Freelance Computational Neuroscience Software Engineer
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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:
Job description
Job Summary:
Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. The ML Engineer will work on deploying trained Machine Learning Models on embedded hardware, optimizing C++ and CUDA code, and collaborating with other engineers to deliver high-quality production code.
Responsibilities:
• Develop modern C++ and CUDA code for AI inference, including data processing algorithms and custom neural network layers
• Optimize C++ and CUDA code guided by timing measurements and profiling to minimize processing latency
• Utilize existing third-party and internal frameworks, libraries and tools
• Work closely with other engineers and domain experts in a collaborative environment
• Write functional and performance tests and documentation
• Deliver high-quality, unit-tested, production code suitable for deployment in embedded, safety-critical environments
Qualifications:
Required:
• Bachelor’s degree in Computer, Electrical, or Software engineering, or advanced degree
• Deep understanding of memory management in C++, error handling, compilers and debuggers on Linux
• Understanding of mechanisms of calling C/C++ functions from Python
• Understanding of neural networks and machine learning
• Strong math skills including linear algebra
• Strong written and verbal technical communication skills
• Positive, team player mindset
Preferred:
• CUDA experience
• Experience with deep learning frameworks such as PyTorch or TensorFlow
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.
Torc Robotics is a leader in autonomous driving technology focused on developing software for automated trucks. The ML Engineer will work on deploying trained Machine Learning Models on embedded hardware, optimizing C++ and CUDA code, and collaborating with other engineers to deliver high-quality production code.
Responsibilities:
• Develop modern C++ and CUDA code for AI inference, including data processing algorithms and custom neural network layers
• Optimize C++ and CUDA code guided by timing measurements and profiling to minimize processing latency
• Utilize existing third-party and internal frameworks, libraries and tools
• Work closely with other engineers and domain experts in a collaborative environment
• Write functional and performance tests and documentation
• Deliver high-quality, unit-tested, production code suitable for deployment in embedded, safety-critical environments
Qualifications:
Required:
• Bachelor’s degree in Computer, Electrical, or Software engineering, or advanced degree
• Deep understanding of memory management in C++, error handling, compilers and debuggers on Linux
• Understanding of mechanisms of calling C/C++ functions from Python
• Understanding of neural networks and machine learning
• Strong math skills including linear algebra
• Strong written and verbal technical communication skills
• Positive, team player mindset
Preferred:
• CUDA experience
• Experience with deep learning frameworks such as PyTorch or TensorFlow
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.
About TORC Robotics
Sourced by ZipRecruiter
Industry
Trucking
Company size
501 - 1,000 Employees
Headquarters location
Blacksburg, VA, US
Year founded
2005