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Founding Machine Learning Engineer Jobs (NOW HIRING)

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Machine Learning Engineer

Fort Mill, SC · Remote

$48/hr

Job Title Machine Learning Engineer Location Remote Rate $48/hr on W2 Must Haves: Neaural networks NLP Python AZURE Pytorch or tensorflow Machine Learning Engineer / AI Engineer Role Role Overview ...

New

Givzey

Machine Learning Engineer

Machine Learning Engineer We're looking for a talented and motivated Machine Learning Engineer to join our team and help develop cutting-edge AI solutions. In this role, you'll have the opportunity ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

The Role We are looking for a Machine Learning Engineer to bridge the gap between AI research and production-grade flight systems. You will optimize, deploy, and scale machine learning models that ...

Northern Base

Machine Learning Engineer

Sunrise, FL · On-site

$90K - $110K/yr

Role - Machine Learning Engineer Experience Required -8+ Years We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs)

Cymertek

Machine Learning Engineer

Aurora, CO · On-site

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative Machine ...

Leash Bio

Machine Learning Engineer

Salt Lake City, UT · On-site

They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

Vultus Inc

Machine Learning Engineer

Honolulu, HI · On-site +1

$110K - $145K/yr

Machine Learning EngineerJob Summary We are looking for a talented Machine Learning Engineer to design, develop, and deploy scalable machine learning models that solve complex business problems. The ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARY We are seeking a talented and innovative ...

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All JobsFounding Machine Learning Engineer Jobs

Founding Machine Learning Engineer information

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$128.8K

$193.5K

How much do founding machine learning engineer jobs pay per year?

As of Jul 29, 2026, the average yearly pay for founding machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a Founding Machine Learning Engineer?

A Founding Machine Learning Engineer is one of the first technical team members at a startup who specializes in designing, building, and deploying machine learning systems. This role involves working closely with the founders to set the technical direction, build core AI products, and establish best practices for data and model development. In addition to hands-on coding and experimentation, a Founding Machine Learning Engineer often influences product decisions and helps shape the company's engineering culture. The role typically requires a blend of deep technical expertise, startup agility, and a willingness to tackle both high-level strategy and low-level engineering tasks.

What engineer makes $500,000 a year?

A founding machine learning engineer at top tech companies or successful startups can earn $500,000 or more annually, often including base salary, bonuses, and equity. Such roles typically require advanced skills in deep learning, data modeling, and experience with large-scale systems, along with a strong track record of innovation and leadership.

What are some unique challenges and expectations for a Founding Machine Learning Engineer in an early-stage startup?

As a Founding Machine Learning Engineer, you'll face the unique challenge of building the company's machine learning infrastructure from the ground up, often with limited resources and rapidly evolving requirements. You'll be expected to wear many hats, from designing and deploying models to setting up data pipelines and collaborating closely with product and engineering teams. Your role will also involve making critical decisions about technology stacks and best practices that will shape the company's technical direction. Additionally, you'll have significant influence on the company's culture and have ample opportunities for growth as the team expands.

What is a founding ML engineer?

A founding machine learning engineer is a key technical team member involved in building and developing the company's initial machine learning systems and infrastructure. They typically have strong skills in programming, data modeling, and deploying ML models, often working closely with product teams during the startup or early-stage company formation. This role requires a combination of technical expertise and entrepreneurial mindset to shape the company's AI capabilities from the ground up.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the increasing adoption of AI and data-driven solutions across industries. They are sought after for their skills in algorithms, programming, and tools like Python and TensorFlow, with job growth expected to continue as AI applications expand.

Which 5 jobs will survive AI?

Founding Machine Learning Engineers are likely to continue playing a crucial role as AI advances, focusing on developing and deploying complex models that require specialized skills in programming, data science, and system architecture. Jobs that involve high levels of creativity, strategic decision-making, and human interaction—such as healthcare professionals, educators, skilled trades, and roles in management—are also expected to persist despite AI automation. These positions typically require emotional intelligence, critical thinking, and adaptability that AI cannot easily replicate.

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

To thrive as a Founding Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, and data science, often supported by a degree in computer science or a related field. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and experience deploying ML models in production are typically required. Strong problem-solving abilities, entrepreneurial mindset, and excellent communication skills set standout candidates apart. These skills and qualities are vital for driving innovation, building scalable solutions from scratch, and collaborating within a fast-paced startup environment.
More about Founding Machine Learning Engineer jobs
What cities are hiring for Founding Machine Learning Engineer jobs? Cities with the most Founding Machine Learning Engineer job openings:
What states have the most Founding Machine Learning Engineer jobs? States with the most job openings for Founding Machine Learning Engineer jobs include:
What job categories do people searching Founding Machine Learning Engineer jobs look for? The top searched job categories for Founding Machine Learning Engineer jobs are:
Founding Machine Learning Engineer jobs near you
Infographic showing various Founding Machine Learning Engineer job openings in the United States as of July 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Machine Learning Engineer

AI Squared

Washington, DC

Other

Re-posted 8 days ago

Job description

Machine Learning Engineer
Washington, DC (Hybrid)

About the Role:

We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying, maintaining, and monitoring the AI/ML systems that power our platform. You will work closely with data scientists, data engineers, and product teams to ensure scalable, reliable, and production-grade AI solutions. You'll play a critical role in operationalizing large language models (LLMs) and other ML systems, ensuring they run efficiently, securely, and with robust monitoring in place.

Key Responsibilities:
  • Design, implement, and maintain ML deployment pipelines for scalable production systems.
  • Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
  • Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
  • Partner with data scientists to transition models from research/prototype into production-ready deployments.
  • Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
  • Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
  • Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
  • Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
  • 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
  • Proven experience deploying and maintaining machine learning models in production at scale.
  • Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
  • Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
  • Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
  • Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
  • Strong understanding of MLOps best practices, monitoring, and automation.
  • Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
  • Strong communication and collaboration skills across technical and non-technical teams.

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