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Manager Spacex Machine Learning Jobs (NOW HIRING)

The hiring manager is specifically looking for someone who enjoys coding and solving technical problems. Key Responsibilities Design, develop, and deploy production-ready Machine Learning models ...

Manage MLOps infrastructure to monitor and optimize models. Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

Manage MLOps infrastructure to monitor and optimize models. Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or production-focused Data Scientist.

... SpaceX. Strong C++ software engineering skills and experience applying machine learning (ML) and AI to simulation solutions are key. Python experience is also required. The team consists of world ...

They are seeking an experienced Machine Learning Engineer to develop and deploy machine learning solutions for autonomous systems, focusing on model optimization and data management. Responsibilities ...

Machine Learning EngineerThe Opportunity Join Adobe and be at the forefront of driving digital ... Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and ...

Machine Learning Engineer The Opportunity Join Adobe and be at the forefront of driving digital ... Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and ...

Implement the full MLOps lifecycle to deploy, operationalize, scale, and manage automated machine learning models and analytical solutions. * Develop and test ML applications according to ...

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Manager Spacex Machine Learning information

What is the difference between Manager Spacex Machine Learning vs Data Scientist Spacex?

AspectManager Spacex Machine LearningData Scientist Spacex
CredentialsAdvanced degrees in CS, ML, or related fields; leadership experienceDegree in CS, Data Science, or related fields; strong analytical skills
Work EnvironmentTeam leadership, project management, strategic planningData analysis, model development, experimentation
Industry UsageOversees ML teams, manages projects, aligns with business goalsBuilds models, analyzes data, provides insights

The main difference is that the Manager Spacex Machine Learning focuses on leading teams and managing ML projects, while the Data Scientist Spacex primarily develops models and analyzes data to support engineering and business decisions.

What cities are hiring for Manager Spacex Machine Learning jobs? Cities with the most Manager Spacex Machine Learning job openings:
What are the most commonly searched types of Spacex Machine Learning jobs? The most popular types of Spacex Machine Learning jobs are:
What states have the most Manager Spacex Machine Learning jobs? States with the most job openings for Manager Spacex Machine Learning jobs include:

Machine Learning Engineer

Waypoint Human Capital

Huntsville, AL • On-site

Other

This job post has expired today. Applications are no longer accepted.


Job description

Position Title: Machine Learning Engineer
Position Type: Full-time, On-Site
Location: Huntsville, AL
Clearance: Active TS
Description:
Waypoint's client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities.
The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration.
Responsibilities:
Integrate machine learning systems into existing software architectures and enterprise platforms
Design, build, and optimize data pipelines to support model training and inference
Develop, test, and deploy machine learning models into production environments
Manage transition from prototype to production, including deployment pipelines and monitoring solutions
Monitor model performance, including handling model drift, rollback, and failure scenarios
Conduct experiments and testing to evaluate and improve model accuracy and performance
Write clean, maintainable, and testable code in Python and related technologies
Collaborate with cross-functional teams to integrate ML capabilities into mission systems
Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control
Support development in Linux and Windows environments
Required:
Active TS clearance (with ability to obtain TS/SCI with CI Polygraph)
Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, or related technical field
Minimum 12+ years of overall experience, including 1-3 years working with machine learning frameworks
Strong programming skills in Python
Experience with machine learning frameworks, libraries, and data modeling techniques
Solid understanding of the machine learning lifecycle
Experience working with SQL and NoSQL databases
Experience working in Linux and Windows environments
Familiarity with CI/CD pipelines and Agile development methodologies
Understanding of software design and system integration principles
Desired:
Active TS/SCI with CI Polygraph (desired)
Experience working with large-scale (petabyte-level) datasets
Experience supporting multi-INT analytics environments
Experience deploying, monitoring, and scaling machine learning models in production
Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub
Experience implementing GitOps workflows
Experience working in secure or classified environment