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Full Stack Machine Learning Engineer Jobs (NOW HIRING)

Inovalon

Senior Machine Learning Engineer

Atlanta, GA

$117.80K - $155.30K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Full Scope

Machine Learning Engineer

Reston, VA

TS/SCI w/ Full-Scope Poly Salary: Competitive We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in ...

Inovalon

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$117.80K - $155.30K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Inovalon

Senior Machine Learning Engineer

Nashville, TN

$118.30K - $156K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves asInovalon'scentral AI and machine learning hub. This team partners with Provider, Payer, and ...

InstantServe LLC

Machine Learning Engineer

Machine Learning Engineer Location: Long Island City, NY 11101 (Onsite 4 Days/week) Type: Permanent ... Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless ...

Apple

Sr. Machine Learning Engineer, Siri Global

Cupertino, CA · On-site

$151.10K - $199.20K/yr

We are particularly interested in "full-stack" machine learning engineers with strong experience in research, software engineering, and have strong leadership potential.You should be passionate about ...

Strava

Machine Learning Engineer

San Francisco, CA

Machine Learning Engineer We are looking for a Machine Learning Engineer to join the growing AI and ... We value full stack ML engineers who are able to work on all parts of an ML pipeline from model ...

Roberts Recruiting

Machine Learning Engineer

Boston, MA · On-site

As a machine learning engineer, you will develop natural language processing systems that help our ... Strong Python skills and Python ML stack (pandas, scikit-learn, numpy, etc.) with knowledge of ...

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Full Stack Machine Learning Engineer information

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$44.5K

$134.8K

$190.5K

How much do full stack machine learning engineer jobs pay per year?

As of Jun 3, 2026, the average yearly pay for full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.

What is a Full Stack Machine Learning Engineer job?

A Full Stack Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models into production. They work across the entire ML pipeline, from data collection and preprocessing to model training, evaluation, and deployment using backend and frontend technologies. This role requires expertise in software engineering, data engineering, and machine learning frameworks like TensorFlow or PyTorch. Additionally, they ensure scalability, reliability, and maintainability of ML systems in real-world applications.

What are the key skills and qualifications needed to thrive in the Full Stack Machine Learning Engineer position, and why are they important?

To thrive as a Full Stack Machine Learning Engineer, you need robust programming skills (Python, JavaScript), a deep understanding of machine learning algorithms, and experience with both backend and frontend development. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, Azure, GCP), and tools such as Docker and Kubernetes, as well as relevant certifications, are highly beneficial. Strong problem-solving abilities, effective communication, and a collaborative mindset are essential soft skills for working across interdisciplinary teams. These competencies are crucial to designing, deploying, and scaling machine learning solutions in production environments while ensuring seamless integration from data to user interface.

What are some typical challenges Full Stack Machine Learning Engineers face, and how do they overcome them?

Full Stack Machine Learning Engineers often encounter challenges such as integrating complex machine learning models into scalable and maintainable production systems, and ensuring efficiency across both backend and frontend components. They must address issues like managing large and varied datasets, optimizing model inference times, and adapting to fast-evolving technologies. Overcoming these hurdles often requires close collaboration with data scientists, DevOps professionals, and product teams, as well as staying updated with best practices in MLOps and system architecture. Being proactive in learning new tools and fostering effective communication are key strategies for success in this dynamic role.
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Full Stack Machine Learning Engineer jobs near you
Infographic showing various Full Stack Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 79% Full Time, 14% Part Time, and 7% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $134,771 per year, or $64.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Infinite Resource Solutions

Atlanta, GA

Other

Posted 22 days ago

Job description

Job Description Machine Learning Engineer Roles and Responsibilities Lead the end-to-end architecture and development of machine learning solutions. Implement machine learning algorithms into services and pipelines to be consumed at large-scale. Engineer large scale development systems using full-stack, distributed shallow and deep-learning technologies and big data technologies.

Architect and develop a highly scalable, distributed, multi-tenant set of microservices backend solutions. Be a part of a highly productive and creative engineering team What Are We Looking For in This Role. Highly Preferred: MS or PhD in Machine learning, Computer Vision, Natural Language Processing or a related field.

5+ years of experience architecting and developing AI and machine learning applications Ability to think critically, question assumptions and devise solutions to challenging technical problems. Hands-on experience with one or more of the following technologies: --Machine Learning: TensorFlow, PyTorch, Spark ML/MLib etc. --ML Technologies: NLP, Computer Vision and related technologies.

--Back end web-services: Java, Spring Boot, Python, Kubernetes, Docker - Big Data technologies: Kafka, Apache Spark, MapR, Hbase, Hive, HDFS etc. Minimum Qualifications Bachelor's Degree Relevant Experience or Degree in: Computer Science, Management Information Systems, Business or related field Typically Minimum 6 Years Relevant Exp Four-year college degree and 6 or more years, and/or a high school diploma with 8 or more years professional experience with full life cycle design and development

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