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Phd Machine Learning Jobs (NOW HIRING)

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Preferred Qualifications MS or PhD in computer vision, computer graphics, machine learning, computer science, computer engineering or related fields. Self-motivated with proven ability to effectively ...

Apple

Machine Learning Engineer, Proactive

Cupertino, CA · On-site

... PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. At least 2 years of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent. Experience with ML/DL algorithms extracting signal from noise. Past experience being able to develop solutions ...

Apple

Machine Learning Engineer, Proactive

Cupertino, CA

$150K - $277K/yr

... PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. At least 2 years of experience in various state-of-the-art techniques related to LLM fine-tuning in 1 or more ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$150K - $277K/yr

As part of our machine learning team, you will play a vital role in prototyping foundational ... Preferred Qualifications MS/PhD in computer vision, electrical, optical or computer engineering or ...

Instacart

OR

Machine learning is central to how we build intelligent shopping experiences at Instacart. We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and ...

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How much do phd machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for phd machine learning in the United States is $22.82, according to ZipRecruiter salary data. Most workers in this role earn between $19.71 and $25.48 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional, and why are they important?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

What is the difference between Phd Machine Learning vs Data Scientist?

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities are hiring for Phd Machine Learning jobs? Cities with the most Phd Machine Learning job openings:
What states have the most Phd Machine Learning jobs? States with the most job openings for Phd Machine Learning jobs include:
Phd Machine Learning jobs near you
Infographic showing various Phd Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $47,468 per year, or $22.8 per hour.
Machine Learning Specialist

Machine Learning Specialist

Applied Physics

New York, NY • On-site

Full-time

Posted 29 days ago

Job description

Applied Physics is seeking a highly motivated and skilled professional to join our Machine Learning team at the Advanced Propulsion Laboratory at Applied Physics. In this role, you will have the opportunity to work on cutting-edge research in new and emerging fields.
Responsibilities:
  • Conduct research on state-of-the-art Machine Learning algorithms relevant to the problem being addressed.
  • Implement, train, and validate proposed algorithms for specific problem domains.
  • Contribute to the integration of algorithms within larger programmatic systems that require these capabilities.
  • Collaborate with others in a multidisciplinary team environment to accomplish research goals.
  • Pursue both independent and collaborative research interests and interact with a broad spectrum of scientists internally and externally to the Laboratory.
  • Publish research results in peer-reviewed scientific journals and present results at conferences, seminars, and meetings.
  • Travel as required to coordinate research with collaborators and visit field sites.

Requirements
  • PhD in Computer Science, Computational Engineering, Applied Statistics, Applied Mathematics, or another technical discipline providing an underlying skillset in data analysis and Machine Learning techniques.
  • Fundamental knowledge of and/or experience developing and applying algorithms in one or more of the following Machine Learning areas/tasks: deep learning, representation learning, zero- or few-shot learning, active learning, reinforcement learning, natural language processing, ensemble methods, statistical modeling and inference (e.g., probabilistic graphical models, Gaussian processes, or nonparametric Bayesian methods).
  • Experience in the broad application of one or more higher-level programming languages such as Python, Java, Scala, or C/C++.
  • Experience with one or more deep learning libraries such as PyTorch, TensorFlow, Keras, or Caffe.
  • Proven ability to undertake original research and communicate findings in peer-reviewed publications.
  • Experience working with a multidisciplinary team of scientists, engineers, and project managers to develop and apply these capabilities to inform engineering decisions.
  • Proficient verbal and written communication skills to collaborate effectively in a team environment and present and explain technical information.

Benefits
We offer a competitive salary and benefits package, flexible work hours, and opportunities for growth and career development. Join our dynamic and passionate team and help us make a positive impact on the world.
If you are a talented, motivated, and empathetic individual who shares our passion for making a difference, we encourage you to apply for this exciting opportunity to work with our team at Applied Physics. Applied Physics is an equal opportunity employer.

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