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Remote Machine Learning Compiler Engineer Jobs in Virginia

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Required Skills: * 5+ years of experience in ML Engineering or Applied Machine Learning. * Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch ...

Niyam IT, Inc.

AI Machine Learning Engineer

Ashburn, VA · On-site +1

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 an Agile team dedicated to productionizing machine learning applications and systems at scale. You ...

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 part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

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Remote Machine Learning Compiler Engineer information

How does a Remote Machine Learning Compiler Engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What is a Remote Machine Learning Compiler Engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

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

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.
What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Virginia? The most popular types of Machine Learning Compiler Engineer jobs in Virginia are:
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Remote Machine Learning Compiler 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

Re-posted 7 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.