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Machine Learning Game Theory Jobs (NOW HIRING)

Spotify

Machine Learning Engineer

Required : • You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in statistics and optimization, especially in sequential ...

Jobs for Humanity

Machine Learning Engineers

San Jose, CA · On-site

$194K - $355K/yr

... and theory in the digitalized world. We provide key insights and technical solutions on privacy ... machine learning algorithms and experienced in federated learning frameworks and applications ...

Gotion, Inc.

Machine Learning Engineer

Fremont, CA · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ... Solid understanding of learning theory concepts such as regularization, generalization, loss ...

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

Role Summary We are seeking a highly motivated Machine Learning Engineer with a strong background ... Solid understanding of learning theory concepts such as regularization, generalization, loss ...

EarnIn

Head of Machine Learning

Mountain View, CA · Hybrid

$477K - $583K/yr

... theoretical concepts with practical implementation. While the role is primarily strategic and ... Define and own the machine learning roadmap in alignment with business goals. * Lead the ML ...

InMobi

Applied Scientist III

San Mateo, CA

We leverage the latest deep learning models alongside classical machine learning techniques to ... Causal inference, decision theory, game theory * Online learning, bandits, RL, Bayesian methods

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... theory, and experimental methodologies • Proficiency in programming languages such as Python, R ...

Q2

Machine Learning Engineer

Austin, TX

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... theory, and experimental methodologies Proficiency in programming languages such as Python, R, or ...

General Atomics

Machine Learning Engineer III

Poway, CA · On-site

$116K - $208K/yr

In both theoretical development environments and specific product design, implementation and ... Adapts machine learning to areas such as virtual reality, augmented reality, artificial ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Hang draws from years of deep expertise in loyalty, game design, and finance with employees from ... This person will implement and develop machine learning models to enhance our platform ...

Quantiply Corporation

Data Scientist

San Jose, CA · On-site

PhD in machine learning, statistics, engineering, mathematics, computer science, neuroscience, bioinformatics, game theory or other technical field. * Strong knowledge of mathematics. * Strong ...

Quantiply Corporation

Data Scientist

San Jose, CA · On-site

PhD in machine learning, statistics, engineering, mathematics, computer science, neuroscience, bioinformatics, game theory or other technical field. * Strong knowledge of mathematics. * Strong ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... The role requires a strong balance between theoretical understanding and engineering execution ...

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How much do machine learning game theory jobs pay per hour?

As of Jun 5, 2026, the average hourly pay for machine learning game theory in the United States is $19.84, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $21.88 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning Game Theory specialist, and why are they important?

To excel as a Machine Learning Game Theory specialist, you need a strong background in mathematics, computer science, machine learning algorithms, and game theory principles, generally supported by an advanced degree in a related field. Proficiency with programming languages such as Python or R, as well as experience with machine learning libraries (e.g., TensorFlow, PyTorch) and game-theoretic modeling tools, is essential. Analytical thinking, problem-solving, and the ability to communicate complex ideas clearly are crucial soft skills in this role. These competencies enable the development of robust models and strategies for real-world applications, driving innovation and effective decision-making.

How do professionals in Machine Learning Game Theory typically collaborate with cross-functional teams to develop robust models?

Professionals in Machine Learning Game Theory often work closely with data scientists, software engineers, and product managers to design and implement models that account for strategic decision-making and adversarial behaviors. Collaboration involves translating theoretical insights into practical algorithms, integrating them with existing machine learning pipelines, and iteratively refining models based on team feedback. Regular meetings and code reviews are common, ensuring that models align with project goals and are robust to real-world uncertainties. This interdisciplinary environment encourages continuous learning and fosters innovation.

What is a Machine Learning Game Theory specialist?

A Machine Learning Game Theory specialist is a professional who applies concepts from game theory—such as strategic decision-making and competition—to machine learning systems. They design algorithms that can anticipate and adapt to the actions of multiple agents, whether those are humans or other AI models. This role is crucial in fields like multi-agent systems, reinforcement learning, economics, and cybersecurity, where predicting and influencing the behavior of others is key. Specialists in this area often work in academia, research labs, or industries developing intelligent systems that must operate in complex, dynamic environments.

What is the difference between Machine Learning Game Theory vs Data Scientist?

AspectMachine Learning Game TheoryData Scientist
Required CredentialsAdvanced degrees in ML, mathematics, or related fieldsDegree in statistics, computer science, or related fields
Work EnvironmentResearch labs, AI development teams, academiaBusiness analytics, data analysis teams, tech companies
Industry UsageAI strategy, multi-agent systems, algorithm developmentData analysis, predictive modeling, business insights

Machine Learning Game Theory focuses on applying game-theoretic principles to machine learning models, often in multi-agent or strategic settings. Data Scientists analyze data to extract insights and build predictive models. While both roles require strong analytical skills and knowledge of machine learning, Machine Learning Game Theory emphasizes strategic interactions in AI systems, whereas Data Scientists focus on data-driven decision making.

Infographic showing various Machine Learning Game Theory job openings in the United States as of May 2026, with employment types broken down into 63% Full Time, 21% Part Time, 1% Temporary, 14% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $41,264 per year, or $19.8 per hour.

Machine Learning Engineer

Spotify

Remote

Full-time

Posted 22 days ago

Job description

Job Summary:
Spotify is a leading company in the music streaming industry, known for its innovative features like Blend and Discover Weekly. They are seeking a Machine Learning Engineer to join their Personalization team, focusing on enhancing user satisfaction through advanced recommendation systems and collaboration with cross-functional teams.
Responsibilities:
• Contribute to designing, scaling/building, evaluating, integrating, shipping, and refining reward signals for recommendations by hands-on ML development.
• Lead collaborations and align across Personalization to integrate and A/B test mid-term signals in various recommendation systems.
• Promote and role-model best practices of ML systems development, testing, evaluation, etc., both inside the team as well as throughout the organization.
Qualifications:
Required:
• You have a strong background in machine learning, enjoy applying theory to develop real-world applications, with expertise in statistics and optimization, especially in sequential models, transformers, generative AI and large language models, and relevant fine-tuning processes.
• You have hands-on experience with large cross-collaborative machine learning projects and managing stakeholders.
• You have hands-on experience implementing production machine learning systems at scale in Java, Scala, Python, or similar languages.
• Experience with PyTorch, Ray, Hugging Face and related tools is required.
• You have some experience with large scale, distributed data processing frameworks/tools like Apache Beam, Apache Spark, or even our open source API for it - Scio, and cloud platforms like GCP or AWS.
• You care about agile software processes, data-driven development, reliability, and disciplined experimentation.
Company:
Spotify is a commercial music streaming service that provides restricted digital content from a range of record labels and artists. Founded in 2006, the company is headquartered in Stockholm, SWE, with a team of 5001-10000 employees. The company is currently Late Stage.

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