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Machine Learning Astronomy Jobs (NOW HIRING)

Rockstar Games

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115.30K - $158.40K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong ... Experience working with pipeline scheduling tools such as Airflow & Astronomer. * Experience ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$124.10K - $163.60K/yr

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong ... Experience working with pipeline scheduling tools such as Airflow & Astronomer. * Experience ...

Rockstar Games

Senior Machine Learning Engineer

Andover, MA · On-site

$105.60K - $145K/yr

They are seeking a Senior Machine Learning Engineer to join their Analytics team, focusing on ... Astronomer. • Experience working with CI/CD tools such as Terraform and GitHub. • Ability to ...

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Machine Learning Astronomy information

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$25.5K

$42.6K

$88K

How much do machine learning astronomy jobs pay per year?

As of Jun 4, 2026, the average yearly pay for machine learning astronomy 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 are the key skills and qualifications needed to thrive as a Machine Learning Astronomer, and why are they important?

To thrive as a Machine Learning Astronomer, you need a strong background in astrophysics, statistical analysis, and programming (often with a PhD in a related field). Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and astronomical data systems is essential. Critical thinking, problem-solving, and effective collaboration are key soft skills for innovating solutions and working within research teams. These skills enable the effective analysis of large astronomical datasets, driving new discoveries and advancements in the field.

What are some common challenges faced by professionals working in machine learning astronomy?

Machine learning astronomers often encounter challenges such as handling extremely large and complex datasets, ensuring data quality, and effectively preprocessing astronomical data to reduce noise and artifacts. Additionally, interpreting model results in a scientific context can be demanding, as it requires both technical expertise and domain knowledge. Collaboration with astronomers, data engineers, and software developers is essential to ensure that machine learning models are both accurate and scientifically meaningful.

What is machine learning astronomy?

Machine learning astronomy is the application of machine learning techniques to analyze and interpret astronomical data. This field combines computer science, statistics, and astronomy to automate tasks such as classifying celestial objects, detecting anomalies, and predicting astronomical events. With the increasing volume of data from telescopes and space missions, machine learning helps astronomers process and extract meaningful insights more efficiently. Researchers in this area develop algorithms that can learn patterns from vast datasets, leading to new discoveries and a deeper understanding of the universe.

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

AspectMachine Learning AstronomyData Scientist
Required CredentialsDegree in Astronomy, Physics, or related fields; knowledge of machine learningDegree in Computer Science, Statistics, or related fields; strong programming skills
Work EnvironmentResearch institutions, observatories, academiaCorporate, tech companies, consulting firms
Industry UsageAnalyzing astronomical data, developing models for celestial phenomenaBusiness analytics, predictive modeling, data visualization

Machine Learning Astronomy focuses on applying machine learning techniques to astronomical data within research settings, while Data Scientists work across various industries analyzing data to inform business decisions. Both roles require strong analytical skills and programming knowledge but differ in domain focus and work environment.

More about Machine Learning Astronomy jobs
What cities are hiring for Machine Learning Astronomy jobs? Cities with the most Machine Learning Astronomy job openings:
What states have the most Machine Learning Astronomy jobs? States with the most job openings for Machine Learning Astronomy jobs include:
What job categories do people searching Machine Learning Astronomy jobs look for? The top searched job categories for Machine Learning Astronomy jobs are:
Machine Learning Astronomy jobs near you
Infographic showing various Machine Learning Astronomy job openings in the United States as of May 2026, with employment types broken down into 50% Internship, and 50% Nights. Highlights an 58% Physical, 1% Hybrid, and 41% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Rockstar Games

New York, NY

$114.30K - $157K/yr

Other

Posted 5 days ago

Job description

At Rockstar Games, we create world-class entertainment experiences.

Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry.

Rockstar Games is on the lookout for a skilled Senior Machine Learning Engineer with strong software development skills who is passionate about games, big data and Machine Learning to join a team that builds Data Science products that directly influences game design, live operations, and player engagement at scale.

This is a full-time, in-office position based out of Rockstar's NYC headquarters in Downtown Manhattan. 

WHAT WE DO
  • The Rockstar Games Analytics team provides insights and actionable results to a wide variety of stakeholders across the organization in support of their decision making.
  • We partner with multiple departments across the company, leveraging analytics to measure and improve on the success and health of our games.
  • We collaborate as a distributed team to develop innovative data pipelines, data products, data models, reports, analyses, and machine learning applications.
  • The Machine Learning Engineering vertical within the Analytics team is tasked with designing, building, and deploying ML systems in addition to advising other verticals on how to design and build reliable, scalable and, fit for purpose models.
RESPONSIBILITIES
  • Partner with Data Scientists and business stakeholders to understand analytical & ML needs and translate them into robust ML solutions that enable us to leverage and derive insights.
  • Design and build end-to-end ML pipelines, including data, features, training and, serving.
  • Push the boundaries of our ML and Data Science platform by taking advantage of and spearheading cutting-edge advancements in AI and Agentic frameworks.
  • Set up monitoring, A/B testing, and metrics frameworks to measure real impact.
  • Perform timely Root Cause Analysis to troubleshoot model and data-related issues; assist in implementation of code and process fixes.
  • Provide thought leadership and collaborate with other team members to continue to scale our architecture to evolve for the needs of tomorrow.
  • Contribute to the technical strategy and establishment of best practices within the team.
  • Develop and support CI/CD processes.
REQUIREMENTS
  • 5+ years of experience building ML systems in production.
  • Bachelor's degree or equivalent in an engineering or technical field such as Computer Science, Mathematics, Statistics, or strong quantitative and software background. 
  • Proven track record in building, monitoring, and optimizing large-scale ML solutions and infrastructure.
  • Experience working in Databricks and Databricks MLflow is essential.
  • Experience working with pipeline scheduling tools such as Airflow & Astronomer.
  • Experience working with CI/CD tools such as Terraform and GitHub.
  • Ability to push the frontier of technology and freely pursue better alternatives.
PLUSES

Please note that these are desirable skills and are not required to apply for the position.

  • Production experience deploying Databricks Genie AI and other Databricks Agentic solutions
HOW TO APPLY

Please apply with a resume and cover letter demonstrating how you meet the skills above. If we would like to move forward with your application, a Rockstar recruiter will reach out to you to explain next steps and guide you through the process.

Rockstar is committed to creating a work environment that promotes equal opportunity, dignity and respect. In line with this commitment, Rockstar will provide reasonable accommodations to qualified job applicants with disabilities during the recruitment process in order for such applicants to be considered for the position for which they are applying, as well as to qualified employees to enable them to perform the essential functions of their roles. If you need more information about Rockstar's reasonable accommodation policies or process, or need to request an accommodation, please notify your recruiter during the interview process.          

If you've got the right skills for the job, we want to hear from you. We encourage applications from all suitable candidates regardless of age, disability, gender identity, sexual orientation, religion, belief, race, or any other protected category.

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