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Entry Level Machine Learning Engineer Jobs in San Francisco, CA

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

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 ...

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$140 - $210/hr

Maintain, monitor, and enhance deployed machine learning systems to ensure continuous improvement. * Collaborate with software engineers, data scientists, and product teams to integrate AI solutions.

Jobzhr

Machine Learning Engineer

Pleasanton, CA · On-site

$110 - $150/hr

... with machine learning frameworks such as TensorFlow, Keras, and PyTorch. Knowledge of cloud platforms and technologies, specifically Microsoft Azure, is crucial. Experience in DevOps and MLOps ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background in model architecture design and algorithm development, ideally with experience in scientific domains ...

Reducto

Machine Learning Engineer

San Francisco, CA · On-site

They are seeking a Machine Learning Engineer to train and deploy critical models for their core product, focusing on interpreting unstructured data and improving model performance. Responsibilities ...

Relace

Machine Learning Engineer

San Francisco, CA · On-site

The Role We're looking for a Machine Learning Engineer who loves getting close to the metal. This is a hands-on engineering role focused on making models faster, more efficient, and more reliable ...

Capable

Machine Learning Engineer

San Francisco, CA · On-site

$150K - $240K/yr

About the Role You will build machine-learning systems that remove real bottlenecks from drug discovery and development. The role spans research and engineering: identifying valuable problems ...

New

Veryfi

Sr. Machine Learning Engineer

San Mateo, CA · On-site

$139K - $184K/yr

Veryfi is seeking a Sr. Machine Learning Engineer who will sit at the intersection of software engineering and data science. The role involves leveraging big data tools to redefine raw data into ...

Elicit

Machine Learning Engineer

Oakland, CA · On-site +1

We invite you to help us build that future. (See how people use Elicit today on Twitter; explore our vision in the roadmap.) About the role As a Machine Learning Engineer at Elicit, you'll build ...

nudge

Machine Learning Engineer

San Francisco, CA · On-site

Define technical strategy and best practices across machine learning, modeling, simulation, and signal processing infrastructure * Mentor and elevate other engineers through technical leadership ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in San Francisco, CA

Entry Level Machine Learning Engineer information

See San Francisco, CA salary details

$35.3K

$81.7K

$139K

How much do entry level machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for entry level machine learning engineer in San Francisco, CA is $81,720.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,700.00 and $92,500.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are the most commonly searched types of Machine Learning Engineer jobs in San Francisco, CA?

The most popular types of Machine Learning Engineer jobs in San Francisco, CA are:

What are popular job titles related to Entry Level Machine Learning Engineer jobs in San Francisco, CA?

For Entry Level Machine Learning Engineer jobs in San Francisco, CA, the most frequently searched job titles are:

What job categories do people searching Entry Level Machine Learning Engineer jobs in San Francisco, CA look for?

The top searched job categories for Entry Level Machine Learning Engineer jobs in San Francisco, CA are:

What cities near San Francisco, CA are hiring for Entry Level Machine Learning Engineer jobs?

Cities near San Francisco, CA with the most Entry Level Machine Learning Engineer job openings:

Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in San Francisco, CA as of August 2026, with employment types broken down into 4% Internship, 84% Full Time, and 12% Contract. Highlights an 74% In-person, 2% Hybrid, and 24% Remote job distribution, with an average salary of $81,720 per year, or $39.3 per hour.

Machine Learning Engineer

Hive

San Francisco, CA • On-site

$120K - $180K/yr

Full-time

Re-posted 4 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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