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Entry Level Edge Ai Machine Learning Jobs (NOW HIRING)

Alignerr

Machine Learning Engineer

Seattle, WA · Remote

Machine Learning Engineer (AI Data Trainer) About the Role What if your expertise in machine ... cutting-edge AI by demonstrating exactly how a skilled technical mind approaches and executes ...

Huzzle

AI Engineer - Remote

... cutting-edge AI initiatives. This is an exciting opportunity for someone passionate about machine learning, generative AI, LLMs, automation, and scalable AI infrastructure in a fully remote ...

Corning

AI/Machine Learning Engineer

Wilmington, NC · On-site

$82K - $112K/yr

Develop and implement AI/ML data science methodologies and AI Products that align with business objectives. * Apply data science techniques, such as machine learning, statistical modeling, and ...

HeyMilo AI

Machine Learning Engineer

Manhattan, NY

Machine Learning Engineer Company: HeyMilo AI Location: New York, NY, USA Contract Details ... AI is a fast-growing startup based in New York City that specializes in developing cutting-edge ...

SynergisticIT

AI and Machine Learning Engineer

Detroit, MI

$104K - $125K/yr

... machine learning libraries and frameworks. * Work within a multidisciplinary team to understand clients business, data, and requirements and develop the appropriate AI or Client solution within our ...

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Entry Level Edge Ai Machine Learning information

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How much do entry level edge ai machine learning jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for entry level edge ai machine learning in the United States is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $18.99 per hour, depending on experience, location, and employer.

Is it entree or entry?

The correct term for the job level is 'entry' level, as in Entry Level Edge AI Machine Learning roles. These positions typically require minimal professional experience and focus on foundational skills in machine learning, AI, and programming tools like Python or TensorFlow. 'Entree' is a culinary term and not related to job levels or roles.

What is the synonym of entry?

In the context of an Entry Level Edge AI Machine Learning position, a synonym for 'entry' is 'initial' or 'beginner,' indicating a role suitable for those starting their careers with minimal experience. These roles often require foundational knowledge of machine learning concepts and basic programming skills, such as Python or TensorFlow.

Is it entry or entery?

The correct term for starting level positions, including Entry Level Edge AI Machine Learning roles, is 'entry' and not 'entery.' Employers typically look for basic skills in machine learning, programming, and AI tools for entry-level roles. Proper spelling ensures clear communication in your application materials.

What does entry mean?

In the context of an Entry Level Edge AI Machine Learning position, 'entry' typically refers to a role suitable for candidates with limited professional experience or recent graduates. It often involves foundational tasks, learning on the job, and may require basic knowledge of machine learning tools and programming languages like Python or TensorFlow.
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What cities are hiring for Entry Level Edge Ai Machine Learning jobs? Cities with the most Entry Level Edge Ai Machine Learning job openings:
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Entry Level Edge Ai Machine Learning jobs near you
Infographic showing various Entry Level Edge Ai Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, 2% Contract, and 1% Nights. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $36,327 per year, or $17.5 per hour.

Sr. AI Machine Learning Engineer

Osv_a10networks

San Jose, CA

$110K - $145K/yr

Full-time

Posted 18 days ago

Job description

Sr. AI Machine Learning EngineerPosition Overview

We are looking for a talented and experienced Deep Learning Engineer specializing in Large Language Models (LLMs) to join our dynamic team. In this role, you will play a pivotal part in enhancing the reliability, safety, and performance of AI models and systems. You will work closely with AI researchers and product teams to drive cutting-edge advancements in AI safety and responsible AI solutions.

Responsibilities

  • Assist in designing and implementing end-to-end safety-focused frameworks for LLMs

  • Develop and apply risk mitigation techniques, including safe inference strategies to ensure reliable AI behavior

  • Identify vulnerabilities in AI systems and contribute to adversarial testing, bias detection, and mitigation strategies

  • Collaborate with cross-functional teams to integrate safety mechanisms into AI workflows and pipelines

  • Design and optimize LLM architectures to improve performance, scalability, and efficiency

  • Fine-tune pre-trained LLMs on domain-specific datasets to improve task performance

  • Stay up to date with the latest research papers, techniques, and advancements in deep learning and related fields

  • Strong software engineering and programming skills, and ability to quickly develop working prototypes from research ideas

Requirements

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field

  • Proven experience in developing and deploying Large Language Models (LLMs), with a focus on architectures such as GPT, BERT, and their variants

  • Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch

  • Knowledge of distributed training techniques and experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud)

  • Excellent problem-solving skills and ability to work independently and in a team environment

  • Strong communication and collaboration skills

AI Use Guidelines for Interviews:Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

Targeted compensation guideline: $110,000 - $145,000. Compensation will vary based on number of factors, including market demand for specific skills, role type, job level, and individual qualifications. Final salary offers are determined by considerations including, but not limited to, subject matter expertise, demonstrated skill level, relevant experience, geographic location, education, certifications, and training.

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