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AI Engineer - Machine Learning 2 Hybrid, Redmond WA -NEED LOCALS at Redmond, Washington, USA
Email: [email protected]
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AI Engineer - Machine Learning 2

Hybrid, Redmond WA -NEED LOCALS

The primary consideration for this position is a preference for candidates with experience in robotics or reinforcement learning, rather than those specializing in natural language models or computer vision.

Our team seeks a Machine Learning Engineer to advance the development and improvement of our software foundation and tools vital for training state-of-the-art AI models. Your role will be centered on creating strong, scalable, and efficient training infrastructures and frameworks facilitating the full spectrum of the machine learning process, from handling data to deploying models. In collaboration with researchers and software engineers, you'll ensure that training systems are smoothly integrated and functioning, expanding the limits of AI's capabilities, especially in practical robotics scenarios. Additionally, you will investigate innovative methods to effectively utilize diverse datasets within our training framework.

Responsibilities

Create and uphold efficient, scalable, and distributed training systemsincluding data preprocessing, training orchestration, and model assessmentfor training large-scale AI models.

Enhance the efficiency of training procedures to improve performance and use of resources, while maintaining scalability and dependability.

Collaborate with researchers to create training and evaluation pipelines for state-of-the-art algorithms.

Develop and design benchmarks for evaluating ML models.

Perform training and and fine-tuning of foundation models for robotic applications .

Monitor and analyze pipelines, identifying bottlenecks and proposing solutions to improve efficiency and performance.

Ensure the robustness and reliability of the training infrastructure, including automated testing and continuous integration.

Preferred Qualifications

BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.

Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.

Strong background in distributed computing, parallel processing techniques, handling large-scale datasets and data preprocessing.

Deep understanding of state-of-the-art machine learning techniques and models.

Experience with cloud-based training environments (AWS, Google Cloud, Azure).

Experience in developing and maintaining software tooling and infrastructure for machine learning.

Deep understanding and practical experience with software engineering principles, including algorithms, data structures, and system design.

Experience with continuous integration and automated testing frameworks.

Candidate Requirements

Years of Experience Required: 2-5 (or 5+ if possible) overall years of experience in the field.

Degrees or certifications required: Bachelor's degree in computer science or related filed is required to be eligible for this role.

Disqualifiers: N/A

Best vs. Average: The ideal resume would contain position as a master's degree student where they worked on robots, reinforcement learning, action models. If has a doctorate or partial doctorate is a plus.

Performance Indicators: Performance will be assessed based on meeting deadlines and quality of work.

Top 3 Hard Skills Required + Years of Experience

1. Minimum 2+ years experience with Linux

2. Minimum 2+years experience with Python

3. Minimum 2+years experience with Configuration management.

In addition:

2+ ROS/ROS2

2+ TensorFlow

2+ Any sort of machine learning packages.

Particular

Details

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Visa status (With validity):

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LinkedIn Profile:

S. LEELA

MADHURI

US IT RECRUITER

Tel:
703-831-8282 Ext.
2518

Email: [email protected]

linkedin.com/in/leela-madhuri-10ab66258

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Keywords: cplusplus artificial intelligence machine learning information technology golang microsoft Idaho Washington
AI Engineer - Machine Learning 2 Hybrid, Redmond WA -NEED LOCALS
[email protected]
[email protected]
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Tue Oct 22 21:04:00 UTC 2024

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