ZipRecruiter

Log In

1

Senior Full Stack Machine Learning Engineer Jobs

OpenReq

Senior Full Stack Engineer

San Francisco, CA · On-site

Mach9 is at the forefront of leveraging advanced machine learning and computer vision techniques to ... They are seeking a Senior Full-Stack Engineer to develop their 3D annotation QA tool, ensuring ...

Mixpeek

Machine Learning Engineer

Washington, DC · On-site

$180 - $240/hr

The business has 10x'd in under two years and has built trust with the senior most leaders at the ... This role requires the ability to contribute to solutions across the full LLM stack, from the OS ...

New

Cypress HCM

Senior Full Stack Engineer

San Jose, CA · Hybrid

$88/hr

Senior Full Stack Engineer Job Details * Senior Full Stack Engineer (Contract) * Location: San Jose CA 95110 (Hybrid) * Duration: 9/15/2025 to 3/13/2026 * Team: US Solutions Enablement Key ...

Citian

Senior Full Stack Engineer

Washington, DC

... Machine Learning to build smarter, more advanced tools for our diverse client base. We work with ... As a Senior Full Stack Engineer at Citian, you'll be expanding current projects and innovating new ...

Citian

Senior Full Stack Engineer

Washington, DC · On-site

... Machine Learning to build smarter, more advanced tools for our diverse client base. We work with ... As a Senior Full Stack Engineer at Citian, you'll be expanding current projects and innovating new ...

previous page

Showing results 41-60

All JobsTechnology JobsSoftware JobsSoftware Developer JobsSenior Full Stack Machine Learning Engineer Jobs

Senior Full Stack Machine Learning Engineer information

See salary details

$44.5K

$134.8K

$190.5K

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

As of Aug 20, 2026, the average yearly pay for senior 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 the difference between Senior Full Stack Machine Learning Engineer vs Data Scientist?

AspectSenior Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Data Science, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops end-to-end ML applications, integrates backend and frontendAnalyzes data, builds models, visualizes insights
Industry UsageTech, finance, healthcare, where deploying ML models is essentialResearch, analytics, consulting across various sectors

While both roles involve working with data and machine learning, the Senior Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, including frontend and backend integration. In contrast, Data Scientists primarily analyze data and develop models to generate insights. The engineer's role is more application-oriented, whereas the Data Scientist's role is more research and analysis-focused.

What cities are hiring for Senior Full Stack Machine Learning Engineer jobs?

Cities with the most Senior Full Stack Machine Learning Engineer job openings:

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs?

The most popular types of Full Stack Machine Learning Engineer jobs are:

What states have the most Senior Full Stack Machine Learning Engineer jobs?

States with the most job openings for Senior Full Stack Machine Learning Engineer jobs include:

Senior Full Stack Machine Learning Engineer jobs near you

Next Insurance - Machine Learning Engineer

Beyond SOF

Atlanta, GA • On-site

Full-time

Re-posted 10 days ago

Job description

Machine Learning Engineer
Experience level: Mid-senior
Experience required: 4 Years
Education level: Bachelor's degree
Job function: Information Technology
Industry: Financial Services
Total position: 1
Relocation assistance: Limited assistance
Visa : Only US citizens and Greencard holders
Job Summary
We are looking for a driven Machine Learning Engineer to help us bring software development rigor to the ML life-cycle within the business insurance industry. As an experienced innovator partnering with the marketing and growth teams, this is a massive opportunity to drive high growth impact at a hyper-growth startup. Your job is to be a full stack ML engineer, supercharging all aspects of scaling Machine Learning at NEXT: application design and architecture, scalable deployment of inference solutions as APIs, data enrichment as a service, and model monitoring.
You will be joining an innovative division of NEXT based in Atlanta: Data Labs. The mandate of Data Labs is to build software and data solutions that meaningfully impact marketing, funnel, risk, and servicing/claims experiences.
What You'll Do:
  • Empower our team of data scientists to rapidly develop and deploy ML solutions.
  • Leverage software engineering best-practices to create and deploy data-intensive and machine learning inference products.
  • Understand the data and dig deep to extract actionable insights.
  • Think creatively and outside the box to answer desired experimental questions as well as exposing opportunities to create business value.
  • Work cross-functionally with marketing, engineering, product, senior management, and external partners.

What We Need:
  • 3+ years of hands-on experience in the complete software development life-cycle with demonstrated professional experience with machine learning
  • Strong command of Python and the standard web development frameworks (e.g. Django, Flask, FastAPI) & fluency with database technologies, SQL, and Python data packages
  • Demonstrated experience deploying models and applications to a cloud environment using tools like Docker and Kubernetes.
  • Demonstrated experience with software engineering best-practices, such as Test-Driven Development and continuous integration/deployment pipelining
  • Experience with ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.)

Unstoppable Qualities:
  • Experience in the insurance industry (strong fintech/lending experience will also be considered)
  • Experience with GitLab

Apply