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Remote Machine Learning Software Engineer Jobs (NOW HIRING)

Cleerly

Sr. Machine Learning Software Engineer

Denver, CO · On-site +1

$126.10K - $166.20K/yr

While we are mostly a remote company, travel is required for some team meetings and cross function ... About the Opportunity We are seeking a senior machine learning software engineer to design, build ...

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... This is a fully remote position, allowing you to work from home or location of record within the U.

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... This is a fully remote position, allowing you to work from home or location of record within the U.

Paylocity

Senior Machine Learning Engineer

$125.40K - $165.30K/yr

The company has become one of the fastest-growing HCM software providers worldwide by offering an ... Working in a collaborative fully remote environment with a desire to share ideas and continuously ...

phData

OR

... Software Engineer, or Data Engineer building and deploying production data and machine learning ... Prior experience working in global or remote teams and partnering across US, LATAM, and/or India.

NSS

Machine Learning Engineer

Concord, NC · Remote

As an ML software developer, you will be responsible for feature development to deliver AI and ... Remote-first environment (if that's your thing) * Dedicated collaborative office space in NoVA (if ...

NSS

Machine Learning Engineer

Concord, NC · Remote

As an ML software developer, you will be responsible for feature development to deliver AI and ... Remote-first environment (if that's your thing) * Dedicated collaborative office space in NoVA (if ...

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 ...

HealthEdge

Machine Learning Engineer

Partner with software engineers to integrate AI into the company's existing software infrastructure ... Work across multiple time zones in a hybrid or remote work environment. * Long periods of time ...

HealthEdge

Machine Learning Engineer

Partner with software engineers to integrate AI into the company's existing software infrastructure ... Work across multiple time zones in a hybrid or remote work environment. * Long periods of time ...

SmarterDx

Staff Software Engineer, Machine Learning

$260K/yr

Role We are looking for a Staff Machine Learning Engineer to help us build a best in class ML ... This role is fully remote within the US** What You'll Do * Build and scale machine-learning driven ...

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 ...

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Remote Machine Learning Software Engineer information

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$63.5K

$147.5K

$205.5K

How much do remote machine learning software engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for remote machine learning software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

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

AspectRemote Machine Learning Software EngineerRemote Data Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, coding, deploying algorithmsAnalyzing data, building models, interpreting results
Industry UsageTech, finance, healthcare, e-commerceTech, finance, healthcare, research institutions

While both roles involve working with data and algorithms, Remote Machine Learning Software Engineers focus on developing and deploying machine learning models through coding, whereas Remote Data Scientists analyze data to extract insights and build statistical models. Both roles often collaborate but serve different primary functions within organizations.

More about Remote Machine Learning Software Engineer jobs
What cities are hiring for Remote Machine Learning Software Engineer jobs? Cities with the most Remote Machine Learning Software Engineer job openings:
What are the most commonly searched types of Machine Learning Software Engineer jobs? The most popular types of Machine Learning Software Engineer jobs are:
What states have the most Remote Machine Learning Software Engineer jobs? States with the most job openings for Remote Machine Learning Software Engineer jobs include:
What job categories do people searching Remote Machine Learning Software Engineer jobs look for? The top searched job categories for Remote Machine Learning Software Engineer jobs are:
Remote Machine Learning Software Engineer jobs near you
Infographic showing various Remote Machine Learning Software Engineer job openings in the United States as of May 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 96% Physical, and 4% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
Machine Learning Software Engineer II

Machine Learning Software Engineer II

Cambium Learning Group

Dallas, TX • On-site, Remote

$89.90K - $123.10K/yr

Full-time

Posted 25 days ago

Cambium Learning Group rating

9.2

Company rating: 9.2 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

12th of 183 rated software companies

Job description

Cambium Learning® Group is an award-winning educational technology solutions leader dedicated to helping all students reach their potential through individualized and differentiated instruction. Using a research-based, personalized approach, Cambium Learning Group delivers SaaS resources and instructional products that engage students and support teachers in fun, positive, safe and scalable environments. These solutions are provided through Learning A-Z® (online differentiated instruction for elementary school reading, writing and science), ExploreLearning® (online interactive math and science simulations, a math fact fluency solution, and a K-2 science solution), Voyager Sopris Learning® (blended solutions that accelerate struggling learners to achieve in literacy and math and professional development for teachers), and VKidz Learning (online comprehensive homeschool education and programs for literacy and science). We believe that every student has unlimited potential, that teachers matter, and that data, instruction, and practice are the keys to success in the classroom and beyond.
Job Overview:
We are seeking a talented Machine Learning Engineer II to join our CAI machine learning and scoring development team. In this role, you will be the crucial bridge between applied research and production systems. Working alongside a cross-functional group of mathematicians, computer scientists, psychometricians, and statisticians, you will design and deploy custom machine learning solutions for our clients and internal platforms.
The ideal candidate is a full-stack ML practitioner who is equally comfortable discussing algorithmic design with researchers and architecting scalable, low-latency production systems. You will own the full software development lifecycle-transforming research prototypes into optimized, production-ready solutions using modern AWS infrastructure such as SageMaker, ECS, and Lambda, with an emphasis on high-throughput inference and PyTorch-to-ONNX model optimization.
Job Responsibilities:
  • Full-Lifecycle ML Development: Lead the transition of machine learning models from theoretical prototypes into scalable, high-performance production systems.
  • AWS Cloud Architecture & Deployment: Architect and deploy ML solutions utilizing AWS ECS (Elastic Container Service) for containerized workloads and AWS Lambda for serverless, event-driven inference pipelines.
  • Model & Inference Optimization: Optimize PyTorch models for production deployment by converting them to ONNX formats. Apply advanced inference optimization techniques (quantization, pruning, ONNX Runtime) and memory-efficient attention mechanisms like Flash Attention to minimize latency and maximize throughput.
  • Infrastructure & Engineering Best Practices: Champion infrastructure best practices for machine learning systems, establishing reliable CI/CD pipelines, and ensuring robust, secure, and reproducible deployments across the AWS ecosystem.
  • Algorithm Engineering: Design, develop, and evaluate algorithms that generate descriptive, diagnostic, predictive, and prescriptive insights from both structured and unstructured data.
  • Robust Software Engineering: Write clean, efficient, and well-tested code. Complete rigorous testing, debugging, and documentation to ensure seamless installation and long-term maintenance.
  • Cross-Functional Collaboration: Actively participate in research discussions, requirements gathering, and system design alongside domain experts to build tailored scoring and ML solutions.

Job Requirements:
  • Experience: 2-5 years of industry experience in Machine Learning Engineering, Software Engineering, or Data Science, with a proven track record of architecting and deploying models to production.
  • Cloud & MLOps Infrastructure: Deep, hands-on experience with the AWS ecosystem, specifically AWS ECS and Lambda. Solid understanding of containerization (Docker) and event-driven architectures.
  • Programming Proficiency: Strong proficiency in modern programming languages used in ML (e.g., Python, C++, Java) and familiarity with industry-standard coding practices.
  • ML Frameworks & Advanced Optimization: Hands-on experience with PyTorch and other machine learning libraries (e.g., Scikit-Learn, TensorFlow). Deep understanding of model optimization pipelines, including PyTorch to ONNX conversions, ONNX Runtime, and scaling attention mechanisms (e.g., Flash Attention).
  • Data Systems: Experience working with large-scale computing frameworks, data analysis systems, and relational/non-relational databases.

Nice to Have's:
  • AWS SageMaker: Experience utilizing AWS SageMaker for managed model training and hosting.
  • Advanced LLMOps & Fine-Tuning: Hands-on experience applying modern parameter-efficient fine-tuning methods (such as LoRA and qLoRA) to large language models.
  • AI Agents: Experience building, integrating, and deploying autonomous or semi-autonomous AI agents to automate complex workflows and connect ML models with external tools/APIs.
  • NLP Expertise: Proven experience and familiarity with deep learning technologies applied specifically to Natural Language Processing (NLP) and complex text-based modeling.
  • Cross-Disciplinary Collaboration: Experience collaborating with specialized researchers (e.g., psychometricians, statisticians) to operationalize complex mathematical concepts.
  • Infrastructure as Code: Experience implementing IaC using tools like Terraform or AWS CloudFormation.
  • Model Monitoring: Experience setting up comprehensive model monitoring systems to detect data drift, concept drift, and model degradation in production AWS environments.

To apply for this opportunity, simply click on the "Apply" button and submit a cover letter and resume.
An Equal Opportunity Employer
We are dedicated to fostering a culture that celebrates unique backgrounds, ideas, and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, gender, gender identity/expression, sexual orientation, national origin, protected veteran status, or disability.

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