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Virtual Aws Machine Learning Jobs in California (NOW HIRING)

AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the ...

AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the ...

The role involves designing, building, and deploying machine learning solutions while collaborating ... with AWS, Kubernetes a bonus • Knowledge of cybersecurity, signals processing, or experience ...

The role involves designing, building, and deploying machine learning solutions into production ... with AWS, Kubernetes a bonus • Knowledge of cybersecurity, signals processing, or experience ...

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift ... Robotics * Familiarity with cloud ML infrastructure (AWS, GCP). * Experience with backend ...

New

About the Role We're looking for a Machine Learning Engineer to design, build, and deploy ... Python, PyTorch, TensorFlow, Scikit-learn, SQL, PostgreSQL, Docker, Kubernetes, AWS, GitHub Actions ...

New

Sr Solutions Architect, Annapurna ML

Cupertino, CA · On-site

$80 - $104.75/hr

AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the ...

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Virtual Aws Machine Learning information

What are the most commonly searched types of Aws Machine Learning jobs in California? The most popular types of Aws Machine Learning jobs in California are:
What cities in California are hiring for Virtual Aws Machine Learning jobs? Cities in California with the most Virtual Aws Machine Learning job openings:

Machine Learning Engineer

MM International

Fremont, CA • On-site

Contractor

Re-posted 6 days ago


Job description

Role: Machine Learning Engineer

Location: Fremont, CA 

 

once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a general video screening with PV. Then we send the submission to the client

About the Role:

Our direct client is hiring a Machine Learning Engineer for their software machine learning and computer vision team to design, develop, and implement critical machine learning models supporting factory and warehouse operations. You will transform ambiguous problem statements into robust end-to-end solutions using a variety of machine learning techniques and tools, including supervised learning, convolutional neural networks, and modern frameworks such as PyTorch and Pandas.

You will collaborate closely with partners in production, process, controls, and quality to deliver solutions for the most challenging problems in our operations. Your work will involve evaluating and deploying models in production environments, ensuring rapid and reliable alerting systems, and addressing operational issues as they arise. You must be adept at handling diverse, heterogeneous datasets that span multiple modalities, including images, multi-spectral sensor outputs, voice, text, and tabular data.

Responsibilities

  • Design, develop, and deploy machine learning models for factory and warehouse environments.
  • Collaborate with cross-functional teams to identify, define, and solve high-impact operational challenges.
  • Build and maintain end-to-end machine learning pipelines, from data collection and preprocessing to model deployment and monitoring.
  • Evaluate and compare models using statistical methods to ensure optimal performance and feasibility.
  • Ensure robust alerting and monitoring systems are in place for deployed models to address issues rapidly.
  • Work with diverse datasets, integrating multiple data types such as images, sensor data, voice, text, and tabular information.
  • Write clean, modular, and sustainable code to translate research ideas into production-ready solutions.

Minimum Requirements

  • In-depth knowledge of Python for high-performance, data-intensive applications.
  • Proficiency with at least one modern deep learning framework (e.g., PyTorch, Jax, TensorFlow).
  • Expertise in one or more of the following areas: computer vision, large language models, recommender systems, or operations research.
  • Foundational knowledge of statistics for model comparison and performance assessment.
  • Real-world experience deploying and maintaining machine learning solutions in production environments.
  • Passion for clean, sustainable, and modular code to bring research concepts to practical implementation.

Preferred Qualifications

  • CI/CD, Kubernetes, MLflow, TensorFlow, PyTorch, AWS.
  • Experience working in manufacturing, industrial automation, or warehouse environments.
  • Familiarity with multi-modal data integration and analysis.
  • Strong problem-solving skills and the ability to thrive in ambiguous, fast-paced settings.
  • Excellent communication skills for cross-functional teamwork.