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Cuda Data Jobs

3 jobs found

20d ago

Data Scientist / Machine Learning Engineer

CorTech Auburn Hills, MI

Auburn Hills, MI

20d ago

Full time Artificial Intelligence Automation Cloud

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Job Description

CorTech is seeking a Data Scientist / Machine Learning Engineer to develop and deploy AI and deep learning solutions for the automotive industry. This onsite role in Auburn Hills, MI focuses on building models for computer vision, predictive maintenance, anomaly detection, and generative AI use cases, working closely with cross-functional partners.

Responsibilities

Design, develop, and deploy AI models for complex automotive problems, including computer vision and generative AI.
Partner with cross-functional teams to understand business challenges and identify opportunities to apply machine learning.
Use generative AI models to support innovation across design, R&D, and manufacturing processes.
Optimize existing machine learning models for performance and scalability using CUDA advanced GPU architectures and parallel computing frameworks for efficient computation.
Design and implement machine learning pipelines for data preprocessing, model training, and evaluation using performance metrics.
Implement machine learning solutions using Python and deep learning frameworks including PyTorch and TensorFlow.
Apply statistical methods and machine learning algorithms to solve complex problems within the automotive domain.
Keep current on advances in data science, machine learning, deep learning, and AI, and apply new approaches to drive continuous innovation.
Develop and maintain documentation for data analysis methods, model development, and deployment processes to support reproducibility and compliance with industry standards.

Requirements

PhD or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Minimum 5 years of experience in a machine learning engineering role, preferably in automotive or a related sector.
Proven experience in machine learning, deep learning, and AI, including developing and deploying models for real-world applications.
Strong understanding of Python, CUDA, and GPU architectures for parallel computing and model optimization.
Solid knowledge of machine learning architectures and techniques, with a focus on computer vision and generative AI.
Proficiency with deep learning frameworks such as PyTorch and TensorFlow.
Experience with parallel computing and optimization for high-performance computing environments.
Ability to collaborate with teams and communicate complex concepts clearly to non-technical stakeholders.
Strong analytical skills to interpret complex data and convert findings into strategic insights and practical solutions.
Self-motivated approach with a commitment to continuous learning and professional development.
Experience working in Agile and with a cloud provider such as Azure is a plus.

Technologies

Python
CUDA
PyTorch
TensorFlow
CUDA advanced GPU architectures
Parallel computing frameworks
Agile
Azure

Location and Work Setting

Auburn Hills, MI (onsite)

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30d ago

Data Scientist / Computer Vision Engineer

Glint Tech Solutions LLC Sunnyvale, CA

Sunnyvale, CA

30d ago Closed

Full time Artificial Intelligence Cloud Cloud Infrastructure

This position is no longer accepting applications (closed Sep 11, 2026).

Job Description

Work on an AI team delivering production-scale computer vision for enterprise applications in Sunnyvale, CA (onsite).

Responsibilities

Design, build, and optimize computer vision solutions for real-world production environments
Create scalable AI inference pipelines using NVIDIA DeepStream
Tune GPU performance to support high-throughput, low-latency computer vision workloads
Develop and deploy distributed computer vision applications across large-scale infrastructure
Design and implement microservices that support AI and computer vision platforms
Collaborate with AI researchers, software engineers, and infrastructure teams to ship production-ready systems
Improve performance, scalability, and reliability across GPU-accelerated environments
Identify and resolve performance bottlenecks by troubleshooting and optimizing inference pipelines

Requirements

Strong experience with computer vision technologies and production deployments
Hands-on NVIDIA DeepStream experience (required)
Strong understanding of GPU optimization and performance tuning
Experience building microservices architecture
Experience with distributed computing systems
Strong programming skills in Python and/or C++
Experience deploying scalable AI applications in production
Excellent problem-solving and performance optimization skills

Technologies

NVIDIA DeepStream, NVIDIA CUDA, TensorRT
Python, C++
OpenCV, GStreamer
Microservices architecture
GPU optimization, NVIDIA SDKs
Kubernetes, Docker
AWS, Azure, GCP, cloud platforms
Machine learning models, deep learning models

Preferred qualifications

Experience with NVIDIA CUDA or TensorRT
Experience with OpenCV, GStreamer, or NVIDIA SDKs
Familiarity with Kubernetes and Docker
Experience with cloud platforms (AWS, Azure, or GCP)
Experience deploying machine learning or deep learning models in production
Knowledge of real-time streaming and edge AI solutions

Required skills (must have)

NVIDIA DeepStream
GPU Optimization
Computer Vision
Microservices Architecture
Distributed Computing

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1mo ago

Principal Machine Learning Engineer, Accelerated Apache Spark

NVIDIA Santa Clara, CA

Santa Clara, CA

1mo ago Closed

$272k - $431k/yr Full time Python Big Data Bigdata

This position is no longer accepting applications (closed Aug 13, 2026).

Job Description

NVIDIA seeks a Principal Machine Learning Engineer to guide ML engineering on the GPU-accelerated Apache Spark program in Santa Clara, focusing on ML-driven performance prediction and optimization for Spark workloads. The role also involves building AI-based deployment tools and providing mentorship across environments. This onsite position offers a salary range of USD 272,000 to 431,250 per year.

Role overview

In this capacity, you will lead the ML engineering efforts for a GPU-accelerated Spark initiative, developing ML-based methods to forecast performance and optimize Spark workloads. You will additionally create AI-enabled tools and provide technical mentorship to enable deployment across diverse environments.

Responsibilities

Design and implement ML solutions for forecasting performance and optimizing GPU-accelerated enterprise Apache Spark workloads.
Develop advanced algorithms and adaptive systems to continually enhance Spark performance on GPUs.
Create AI-driven agents and tools to assist with diagnosing system issues and optimizing applications.
Collaborate with partners and customers to deploy complex ML solutions across varied environments.
Maintain deep domain expertise by staying current with the latest advances in ML systems and algorithms.
Provide technical leadership and mentorship in data science and ML for a team of engineers.

Requirements

Education: BS, MS, or PhD or equivalent experience in Machine Learning, Data Science, Computer Science, or a closely related field.
12+ years of professional experience designing, implementing, and productionizing high-quality ML/DL solutions.
5+ years of experience as a technical lead in ML model development.
Proven hands-on experience (2+ years) with large-scale data processing platforms such as Apache Spark.
Demonstrated ability to apply modern tooling and robust practices across all stages of building, deploying, and maintaining ML models.
Excellent programming skills in Python and related data science libraries (NumPy, pandas, scikit-learn, SciPy, PyTorch, TensorFlow).
Deep expertise in advanced ML methodologies, including LLMs/GenAI, reinforcement learning, and adaptive online ML systems.
Strong capability in feature engineering, feature importance assessment, and developing boosted tree models (e.g., XGBoost).

Technologies

Python
NumPy
pandas
scikit-learn
SciPy
PyTorch
TensorFlow
Apache Spark
XGBoost
Scala
Java
C++
CUDA

Benefits

Equity and benefits

Ways to stand out from the crowd

Understanding of the internal workings and architecture of Apache Spark
Familiarity with NVIDIA GPUs and CUDA
Experience coding in Scala, Java, and/or C++

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Cuda Data Jobs

Data Scientist / Machine Learning Engineer

Data Scientist / Computer Vision Engineer

Principal Machine Learning Engineer, Accelerated Apache Spark

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