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Work From Home Machine Learning Jobs in Washington, DC

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Remote, work-from-home career * Average first-year earnings of $69K through commissions and bonuses * Increased earning potential in later years through performance and renewals * Residual income ...

Showing results 41-60

Work From Home Machine Learning information

See Washington, DC salary details

$28.9K

$48.2K

$99.7K

How much do work from home machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for work from home machine learning in Washington, DC is $48,230.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,800.00 and $52,100.00 per year, depending on experience, location, and employer.

What is a work from home machine learning job?

A Work From Home Machine Learning job allows professionals to develop, train, and deploy machine learning models remotely. These roles typically involve tasks such as data preprocessing, model selection, optimization, and performance evaluation. Common industries for remote ML jobs include tech, healthcare, finance, and e-commerce. Strong programming skills in Python, experience with ML frameworks like TensorFlow or PyTorch, and familiarity with cloud platforms are often required. Remote ML engineers collaborate with data scientists, software engineers, and business analysts to create AI-driven solutions.

What are the main challenges of working remotely in a machine learning role?

One of the main challenges of working remotely in a machine learning role is maintaining effective collaboration and communication with team members across different locations and time zones. Without face-to-face interactions, it can be more difficult to brainstorm, review complex models, or debug issues collaboratively. To overcome these obstacles, remote machine learning professionals frequently use project management tools, version control systems, and video conferencing to stay in sync with their teams. Strong self-motivation, proactive communication, and time management are essential for staying productive and connected while working from home.

What are the key skills and qualifications needed to thrive in a work from home machine learning position?

To thrive as a Work From Home Machine Learning professional, you need a strong background in mathematics, programming (Python or R), and experience with machine learning algorithms, typically backed by a degree in computer science or related fields. Technical proficiency with tools like TensorFlow, PyTorch, scikit-learn, and cloud platforms such as AWS or Azure, as well as relevant certifications, is highly valuable. Excellent communication, problem-solving abilities, and self-discipline help you collaborate remotely and manage projects independently. These skills ensure you can effectively build and deploy models, overcome technical challenges, and contribute to distributed teams in a virtual setting.

Machine Learning Engineer with SageMaker Experience

Maxiom Technology

Ashburn, VA • On-site, Remote

Full-time

Re-posted 18 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.