Build a machine learning platform/application for the end-to-end machine learning lifecycle: rapid prototyping; full-scale training; deploying, monitoring, maintaining models; and iterating on modeling ideas based on user feedback. Collaborate with business to understand their requirements, collect ...
Investigate the machine learning methodologies, including deep learning, LLM, and graph NN, to address diverse challenges across different business verticals and customers. We are hiring a Leader of Machine Learning Engineering to work on our GenAI platform transforming the lives of all our customer...
The Staff MLOps Engineer will lead the design, development, and implementation of scalable machine learning operations (MLOps) pipelines and infrastructure. This role is critical for ensuring that machine learning models are efficiently deployed, monitored, and maintained in production environments....
Knowledge and application of machine learning including unsupervised learning, supervised learning, and reinforcement learning. Knowledge and application of supervised learning methods and models such as linear regression, logistic regression, decision forest, gradient boosted trees, support vector ...
Experience and good understanding of Machine Learning / Deep Learning Models / Python / ML Model Deployment / ML Model Management for production environments. Understanding or desire to learn end to end Machine Learning technology stack (Tools such as Kubeflow, Kubernetes, SeldonCore, H2O, Data Robo...
Senior Machine Learning Engineer. As a Senior Machine Learning Engineer, you will be responsible for building and deploying the AI models needed for our projects. Deploy machine learning models for our AI solutions. Optimize machine learning models for accuracy, efficiency, and scalability. ...
Artificial Intelligence/Machine Learning Programmer [ No C2C or OPT -00000 ]. ...
REMOTE Senior ML Ops Engineer / Lead Machine Learning Engineer Needed for Growing Subsidiary of a Large Public Company!. As a Lead ML Engineer / Senior Machine Learning Engineer in our company, we are able to offer:. As a Lead Machine Learning Operations Engineer / Lead MLOps Engineer on our team, w...
Artificial Intelligence/Machine Learning Programmer [ No C2C or OPT -00000 ]. ...
Solid understanding of machine learning techniques and algorithms, such as HMM, neural networks, deep learning, etc. Experience with a machine learning platform such as: TensorFlow, Caffe, Keras, or Encog. ...
Build a machine learning platform/application for the end-to-end machine learning lifecycle: rapid prototyping; full-scale training; deploying, monitoring, maintaining models; and iterating on modeling ideas based on user feedback. Collaborate with business to understand their requirements, collect ...
Experience and good understanding of Machine Learning / Deep Learning Models / Python / ML Model Deployment / ML Model Management for production environments. Specialized Area: Machine learning. Understanding or desire to learn end to end Machine Learning technology stack (Tools such as Kubeflow, Ku...
Artificial Intelligence/Machine Learning Programmer [ No C2C or OPT -00000 ]. ...
Specialized Area: Machine Learning. The Intern will be supporting machine learning algorithm development of object and environment perception for autonomous driving vehicles. The tasks of the position include but are not limited to annotation of data collected from autonomous vehicles, testing and v...
Work with fellow data scientists and machine learning developers to establish standards. ...
Machine Learning Policy - Technical Expert We are the movers of the world and the makers of the future. Are y Technical, Policy, Machine Learning, Computer Science, Technology, Expert, Manufacturing. ...
GenAI/Machine Learning certification. GenAI/Machine Learning solutions. From on-the-job learning experiences to formal development programs, our professionals have a variety of opportunities to continue to grow throughout their career. ...
Machine Learning Engineer role resides within the Ford’s Electric Vehicle organization. Data engineering, data product development and software product launches At least three of the following languages: Java, Python, Spark, Scala, SQL Developing Machine Learning algorithms working with Data Scienti...
The Staff MLOps Engineer will lead the design, development, and implementation of scalable machine learning operations (MLOps) pipelines and infrastructure. This role is critical for ensuring that machine learning models are efficiently deployed, monitored, and maintained in production environments....
Learning - Participates in learning activities around modern software design, machine learning, and development core practices (communities of practice); Proactively views articles, tutorials, and videos to learn about new technologies and best practices being used within other technology organizati...
Responsibilities includes, but are not limited to the following:.Design, build, deploy, monitor and support production deployment of data science solutions.Research and implement ML algorithms and tools as a proof-of-concept and move it to the production-ready state.Select appropriate datasets and d...
Be the resident expert and continuously monitor the SOTA in machine learning (ML), deep learning (DL), reinforcement learning (RL) and multi-modal perception methods as enablers for a variety of Autonomous system applications. Senior Staff Machine Learning Engineer,. This position is a perfect match...
Ford's GDI&A department is on the hunt for talented individuals skilled in Machine Learning, Big Data, Statistics, Econometrics, and Optimization. We're looking for exceptional Machine Learning and AI scientists who are eager to engage in all project stages, from problem identification to model depl...
Experience with machine learning frameworks. At our company, we focus on developing and maintaining AI and computer/machine vision solutions. ...
Knowledge and application of machine learning including unsupervised learning, supervised learning, and reinforcement learning. Knowledge and application of supervised learning methods and models such as linear regression, logistic regression, decision forest, gradient boosted trees, support vector ...