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Staff Machine Learning Engineer Jobs (NOW HIRING)

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

About the Role We are seeking an exceptional Staff Machine Learning Engineer to lead the design and development of the next generation of our AI-driven fraud detection platform . You will architect ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

Staff Machine Learning Engineer Compensation: $265,000 - $280,000 base + equity Location: San Francisco, hybrid 3 days per week Join a fast-growing AI technology company building the infrastructure ...

Xometry is looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact.

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

We are looking for a great Staff Machine Learning Engineer to join our seasoned AI team and lead the development of Edge AI for in-vehicle self-aware health monitoring and prediction. In this role ...

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Staff Machine Learning Engineer information

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$23K

$99.3K

$192.5K

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

As of Sep 4, 2026, the average yearly pay for staff machine learning engineer in the United States is $99,330.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,000.00 and $125,000.00 per year, depending on experience, location, and employer.

What is a staff machine learning engineer?

A Staff Machine Learning Engineer is a senior-level technical role responsible for designing, deploying, and optimizing machine learning models at scale. They provide technical leadership, mentor other engineers, and drive best practices in ML system architecture. This role often involves collaborating with cross-functional teams, improving model performance, and ensuring the reliability of machine learning solutions in production. Staff ML Engineers typically have deep expertise in algorithms, data infrastructure, and engineering processes. Their work focuses on solving complex problems and influencing the broader ML strategy within an organization.

What are the typical collaboration and leadership responsibilities for a staff machine learning engineer?

As a Staff Machine Learning Engineer, you often serve as a technical leader, partnering with cross-functional teams including data scientists, product managers, and software engineers to develop and deploy machine learning solutions. You will mentor junior engineers, conduct code reviews, and help establish best practices for model development and deployment. In addition to hands-on technical work, you may be responsible for evaluating new tools, contributing to the broader ML strategy, and facilitating knowledge sharing sessions. This collaborative and leadership-focused approach helps ensure consistency, quality, and innovation across machine learning projects.

What are the key skills and qualifications needed to thrive in the staff machine learning engineer position, and why are they important?

To thrive as a Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, data analysis, and typically a strong academic background in computer science or related fields. Experience with Python, TensorFlow, PyTorch, cloud platforms, and a track record of delivering production-level ML systems are crucial, as are advanced degrees or relevant certifications. Strong leadership, communication, and mentoring skills help you effectively guide teams and collaborate across departments. These competencies are essential for designing robust ML solutions, leading technical initiatives, and ensuring successful project delivery in complex organizational environments.

Do staff machine learning engineers get paid well?

Staff machine learning engineers typically earn high salaries due to their advanced skills, experience, and expertise in developing complex models and deploying AI solutions. Compensation often includes base salary, bonuses, and stock options, reflecting their seniority and impact within organizations.
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Infographic showing various Staff Machine Learning Engineer job openings in the United States as of August 2026, with employment types broken down into 2% As Needed, 76% Full Time, 16% Part Time, 1% Temporary, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $99,330 per year, or $47.8 per hour.

Staff Machine Learning Engineer

Hive

San Francisco, CA • On-site

$200K - $300K/yr

Full-time

Re-posted 19 days ago


Job description

About Hive
Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.
Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!
Staff Machine Learning Engineer
In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.
Responsibilities
  • Everything involved in applying a ML model to a production use case, including designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
  • Write and maintain scalable, performant code that can be shared across platforms
  • Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
  • Improve engineering standards, tooling, and processes
  • Develop novel, accurate, and performant ML algorithms for use at scale
  • Conduct metric-driven research experiments to improve model performance
  • Provide mentorship to and help onboard ML engineers
  • Lead cross-functional collaboration with other teams
  • Contribute to defining strategic direction, planning the roadmap
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Minimum Requirements
  • You have a Bachelor's Degree in computer science or a related field
  • You have 8+ years of experience building web applications
  • You have successfully implemented highly-available distributed systems/microservices
  • You have delivered scalable backend APIs
  • You have strong interpersonal and communication skills with a bias towards action
  • You have experience writing code and training across distributed systems
  • You have the ability to understand and make well-reasoned tradeoffs in designing features
  • You are an expert in machine learning frameworks, such as PyTorch or Tensorflow
  • You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
  • You are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
  • You can lead end to end development of new products

Who We Are
We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.
Thank you for your interest in Hive and we hope to meet you soon!
The current expected base salary for this position ranges from $200,000 - $300,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.