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Graduate Machine Learning Jobs (NOW HIRING)

Hive

Machine Learning Engineer

San Francisco, CA

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics * You have 1-2 years industry machine learning ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

Desired Qualifications * 2-8+ years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing-or a strong recent graduate with ...

Alljoined

Machine Learning Researcher

San Francisco, CA · On-site

$140K - $250K/yr

You will design and implement advanced machine learning models for EEG-based neural decoding ... A graduate degree (M.S. or Ph.D.) in computer science or a related field-such as artificial ...

Spotter

Machine Learning Scientist

Culver City, CA · On-site

Experience with reinforcement learning or contextual bandit systems gained through graduate ... Expertise in training, evaluating, tuning, and deploying machine learning models across deep ...

TEKsystems

Machine Learning Engineer

Chicago, IL · On-site +1

$95 - $105/hr

... graduate from UCLA with 2-3 years at Snapchat in the ML domain, or experience with Walmart e ... Applying the latest techniques and approaches across the domains of data science, machine learning ...

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Graduate Machine Learning information

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$25.5K

$42.6K

$88K

How much do graduate machine learning jobs pay per year?

As of Aug 19, 2026, the average yearly pay for graduate machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a graduate machine learning?

A Graduate Machine Learning job is an entry-level role designed for recent graduates with a background in machine learning, data science, or a related field. It typically involves working on data-driven projects, developing machine learning models, and assisting in research or engineering tasks. Graduates may collaborate with data scientists, software engineers, and business teams to design algorithms, optimize models, and deploy AI solutions. This role helps build practical experience in applying ML techniques to real-world problems while contributing to the organization's AI initiatives.

What does the typical career progression look like for a graduate machine learning?

As a Graduate Machine Learning professional, you will usually begin your career by working on smaller projects or supporting senior scientists with data preparation, model training, and performance evaluations. Over time, as you gain experience and demonstrate technical proficiency, you’ll be given more complex, independent projects and may specialize in areas like natural language processing, computer vision, or deep learning. Many organizations provide opportunities for mentorship, professional development, and advanced certifications, paving the way for roles such as Machine Learning Engineer, Data Scientist, or Research Scientist. This path offers significant opportunities for growth, both in terms of technical expertise and leadership potential.

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

To thrive as a Graduate Machine Learning professional, you need a solid understanding of statistics, data analysis, machine learning algorithms, and programming languages such as Python or R, typically supported by a relevant degree. Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch), data visualization tools, and version control systems like Git is common. Strong problem-solving abilities, communication skills, and a collaborative mindset will help you stand out in team-based environments. These competencies are vital for effectively building, analyzing, and refining models to address real-world business challenges.

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Graduate Machine Learning jobs near you
Infographic showing various Graduate Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Hive

San Francisco, CA

$120K - $180K/yr

Full-time

Re-posted 17 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!
 
Machine Learning Role
 
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
  • Interface closely with the Backend and DevOps teams as well as with our internal data labeling services
  • Utilize OWASP top 10 techniques to secure code from vulnerabilities
  • 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
Requirements
  • You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics
  • You have 1-2 years industry machine learning experience
  • You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project
  • You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others
  • You know the ins and outs of Python, especially as it applies to the above ML frameworks
  • You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
  • You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, SQL, Cassandra, Docker
  • You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
  • You have great communication skills and ability to work with others
  • You are a strong team player, with a do-whatever-it-takes attitude
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 $120,000 - $180,000. 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.
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