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Remote Google Machine Learning Engineer Jobs in Virginia

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site +1

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

NT Concepts

Machine Learning Engineer

Chantilly, VA · On-site +1

Vienna, VA and Chantilly, VA with remote flexibility Responsibilities: As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning applications and software systems ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

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Remote Google Machine Learning Engineer information

What is a Remote Google Machine Learning Engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

What are the key skills and qualifications needed to thrive as a Remote Google Machine Learning Engineer, and why are they important?

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do Remote Google Machine Learning Engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.
What are the most commonly searched types of Google Machine Learning Engineer jobs in Virginia? The most popular types of Google Machine Learning Engineer jobs in Virginia are:
What are popular job titles related to Remote Google Machine Learning Engineer jobs in Virginia? For Remote Google Machine Learning Engineer jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Remote Google Machine Learning Engineer jobs in Virginia look for? The top searched job categories for Remote Google Machine Learning Engineer jobs in Virginia are:
What cities in Virginia are hiring for Remote Google Machine Learning Engineer jobs? Cities in Virginia with the most Remote Google Machine Learning Engineer job openings:
Remote Google Machine Learning Engineer jobs near you
Machine Learning Engineer with SageMaker Experience

Machine Learning Engineer with SageMaker Experience

Maxiom Technology

Ashburn, VA • On-site, Remote

Full-time

Posted 16 days ago

Job description

Are you a passionate Machine Learning Engineer with a strong background in SageMaker, prompt engineering, and LLM (Large Language Model) model tuning? Do you thrive in a dynamic and innovative environment, eager to push the boundaries of AI capabilities? If so, we invite you to join our team as we revolutionize the world of AI-driven applications.

Position: Machine Learning Engineer
Location: Remote

Preferred Resource Location: LATAM

About Us:
Maxiom Technology is a cutting-edge technology company at the forefront of AI-driven solutions. We specialize in developing intelligent applications that leverage the power of machine learning and natural language processing. Our team consists of talented individuals who are dedicated to creating groundbreaking solutions that transform industries.

Responsibilities:

- Collaborate with cross-functional teams to design, develop, and deploy machine learning models using Amazon SageMaker.
- Utilize your expertise in prompt engineering to craft effective inputs for LLM models to achieve desired outputs.
- Fine-tune and optimize LLM models to enhance performance, efficiency, and accuracy.
- Design and implement experiments to evaluate model performance, iteratively improving results.
- Stay up-to-date with the latest advancements in machine learning, particularly in the realm of LLM models and prompt engineering techniques.
- Identify and troubleshoot issues related to model performance, data quality, and integration.
- Contribute to the entire machine learning lifecycle, from data preprocessing and training to deployment and monitoring.
- Collaborate with software engineers to integrate machine learning solutions into our applications.
- Document your work, best practices, and findings to share knowledge across the team.

Qualifications:

- Bachelor's degree in Computer Science, Engineering, or a related field (Master's or PhD preferred).
- Proven experience in developing and deploying machine learning models using Amazon SageMaker.
- Strong background in prompt engineering techniques for fine-tuning LLM models.
- Proficiency in programming languages such as Python for model development and experimentation.
- Solid understanding of natural language processing concepts and techniques.
- Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and their integration with SageMaker.
- Experience with data preprocessing, feature engineering, and data augmentation.
- Problem-solving skills to diagnose and address model performance and data-related issues.
- Excellent communication skills to collaborate effectively within multidisciplinary teams.
- Ability to adapt to evolving technologies and learn quickly in a fast-paced environment.

Bonus Skills:

- Publications or contributions to the machine learning community.
- Experience with cloud services (AWS, Azure, Google Cloud) and containerization technologies.
- Knowledge of DevOps practices for model deployment and monitoring.

Why Join Us:

- Opportunity to work on cutting-edge projects that push the boundaries of AI technology.
- Collaborative and inclusive work environment that values innovation and creativity.
- Access to resources and support for continuous learning and professional growth.
- Competitive compensation package and benefits.

If you are an ambitious Machine Learning Engineer with a proven track record in SageMaker, prompt engineering, and LLM model tuning, we would love to hear from you. Join us in our mission to create groundbreaking AI solutions that shape the future. Apply now by sending your resume and a cover letter.

Maxiom Technology is an equal opportunity employer. We encourage applications from candidates of all backgrounds and experiences.