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Machine Learning Astronomy Jobs in Michigan (NOW HIRING)

Machine Learning Astronomy information

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.

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 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 cities in Michigan are hiring for Machine Learning Astronomy jobs? Cities in Michigan with the most Machine Learning Astronomy job openings:
ADAS Cloud Infrastructure Engineer

ADAS Cloud Infrastructure Engineer

Ford Motor Company

Dearborn, MI • Hybrid

$113K - $190K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 11 days ago


Job description

In this position... 

You will be a part of the team building the ADAS teams cloud-native tools, services and pipelines on which our product teams depend. You will develop software within the distributed ecosystem that continuously feeds back data and improve our products. You will work cross functionally with data operations, algorithm development, and vehicle platform teams to create containerized services and workflows which support all phases of the data and machine learning life cycle. The person in this position will provide technical leadership in an expanding team and role model Agile and DevOps principles to develop technologies needed to design, test, validate, and deploy software at scale.

You'll have...

  • Bachelor's or foreign equivalent degree in computer science, electrical engineering or a related field

  • 3 years' experience architecting, developing and testing web applications in complex systems

  • 3 years' experience developing web applications using REST architecture

  • 3 years' experience developing enterprise applications using relational and NoSQL databases

  • 1 year experience using cloud-native containerization and orchestration technologies (e.g. Docker, Kubernetes, Airflow, Astronomer)

  • Fluency in Python

Even better, you may have...

  • Master's or foreign equivalent degree in computer science, electrical engineering or a related field

  • 5+ years developing production micro-services and APIs

  • 3+ years of experience with Agile software development processes

  • 1+ years developing MLOps services and automation workflows  

  • 1+ year with scale processing tools (PySpark, Iceberg, Databricks)

  • 1+ year of experience with data compliance, sandboxing, and observability 

  • Proven ability to deliver complex solutions in an intensely collaborative product creation environment

  • Excellent written and verbal communication skills, both vertically and horizontally within the organization

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service 
A generous schedule of paid holidays, including the week between Christmas and New Year's Day 
Paid time off and the option to purchase additional vacation time. 

This position is a salary grade 5 and ranges from $66,660-$112,020., This position is a salary grade 6 and ranges from $83,280-139,680., This position is a salary grade 7 and ranges from $97,140-162,540., This position is a salary grade 8 and ranges from $113,580-190,500.     
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
For more information on salary and benefits, click here: https://fordcareers.co/GSR

Visa sponsorship is not available for this position.

Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.

This position is hybrid. Candidates who are in commuting distance to a Ford hub location may be required to be onsite four or more days per week. #LI-Hybrid

   #LI-LB1 

What you'll do...

  • Design the data pipelines and engineering infrastructure to support our ADAS products

  • Full stack development of web applications to support a transparent and user friendly ADAS data platform

  • Workflow automation and scaling using GCP tools (TerraForm,DataFlow, Vertex AI, CloudRun, GKE)

  • System integration testing and deployment to production environment

  • Cloud infrastructure provisioning and management

  • Be part of our culture of continuous improvement and proactive ownership. Identify efficiency gaps, and drive productivity improvements.
  • Execute best practices in version control and CI/CD

  • Collaborate with algorithmic teams developing early product concepts and operationalize their prototype ML environments and pipelines.
  • Formulate KPIs for our cloud services and pipelines, and integrate telemetry to measure and track efficiency
  • Stay current on the latest tools and trends in the cloud software domain

Ford logo

About Ford

Sourced by ZipRecruiter

At Ford Motor Company, we believe freedom of movement drives human progress. With our incredible plans for the future of mobility, we have a wide variety of opportunities for you to accelerate your career and help us define tomorrow's transportation.

Industry

Civil engineering construction

Company size

51 - 200 Employees

Headquarters location

Doral, FL, US

Year founded

1982