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Remote Spacex Machine Learning Jobs in Virginia (NOW HIRING)

Halvik

Machine Learning Engineer - Remote

Vienna, VA · On-site +1

$140K - $150K/yr

Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning ...

Niyam IT, Inc.

AI Machine Learning Engineer

Ashburn, VA · On-site +1

Remote Work: Niyam understands the value of flexibility. We offer remote work. * Career Growth ... The ideal candidate brings a strong foundation in machine learning, data engineering, and MLOps ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Maintain current in emerging tools and techniques in machine learning, statistical modeling, and ... Washington DC Metro Area - Remote (candidates MUST BE located in the National Capital Region - DMV ...

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Remote Spacex Machine Learning information

What does a Remote SpaceX Machine Learning Engineer do?

A Remote SpaceX Machine Learning Engineer uses data-driven algorithms and models to solve complex problems for SpaceX, often focusing on areas such as rocket manufacturing, satellite communications, and mission planning. Working remotely, these engineers collaborate with cross-functional teams to design, develop, and implement machine learning solutions that improve efficiency, safety, and performance. They may analyze large datasets, build predictive models, and deploy AI systems to support SpaceX's ambitious goals in space exploration.

What are some unique challenges of working remotely as a Machine Learning Engineer at SpaceX, and how can candidates prepare for them?

Working remotely as a Machine Learning Engineer at SpaceX presents unique challenges such as collaborating across distributed teams, managing time zones, and maintaining effective communication with colleagues involved in hardware and aerospace projects. To succeed, candidates should be proactive in seeking regular updates, use collaborative tools efficiently, and be comfortable working independently while still aligning with team objectives. Familiarity with remote development environments and a strong ability to document and present complex models are also key to thriving in this role.

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

AspectRemote Spacex Machine LearningRemote Spacex Data Scientist
Required CredentialsAdvanced degree in Computer Science, AI, or related field; experience in ML frameworksDegree in Data Science, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, algorithms, and AI systems for space applicationsAnalyzing data, creating insights, and supporting decision-making processes
Employer & Industry UsageUsed in AI-driven space missions, autonomous systems, and roboticsApplied in data analysis, reporting, and predictive modeling for space projects

Remote Spacex Machine Learning specialists focus on developing AI models for space technology, while Data Scientists analyze data to inform decisions. Both roles require strong technical skills and often collaborate but serve different core functions within the industry.

What are the key skills and qualifications needed to thrive as a Remote SpaceX Machine Learning Engineer, and why are they important?

To excel as a Remote SpaceX Machine Learning Engineer, you need strong expertise in machine learning, data analysis, and programming languages like Python, along with a relevant degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud computing platforms, and version control systems is typically necessary, and certifications in machine learning or data science can be advantageous. Excellent problem-solving skills, strong communication, and the ability to collaborate remotely are key soft skills that help you stand out. These skills ensure you can develop robust ML models that support SpaceX’s technical goals while effectively working within distributed teams.
What are the most commonly searched types of Spacex Machine Learning jobs in Virginia? The most popular types of Spacex Machine Learning jobs in Virginia are:
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What cities in Virginia are hiring for Remote Spacex Machine Learning jobs? Cities in Virginia with the most Remote Spacex Machine Learning job openings:
Remote Spacex Machine Learning jobs near you
Machine Learning Engineer - Remote

Machine Learning Engineer - Remote

Halvik

Vienna, VA • On-site, Remote

$140K - $150K/yr

Full-time

Posted 8 days ago

Job description

Halvik Corp delivers a wide range of services to 13 executive agencies and 15 independent agencies. Halvik is a highly successful WOB business with more than 50 prime contracts and 500+ professionals delivering Digital Services, Advanced Analytics, Artificial Intelligence/Machine Learning, Cyber Security and Cutting Edge Technology across the US Government. Be a part of something special!
Role and Responsibilities
Model Development
  • Collaborate with data scientists and SMEs to develop ML models using curated datasets.
  • Conduct experiments, prototypes, and proof-of-concepts to validate model performance.
  • Create scalable and reusable training pipelines using Databricks notebooks and MLflow.

Implementation and Optimisation
  • LLMs (Large Language Models), RAGs, and AI agent systems for various business applications. Deployment & MLOps
  • Operationalize models with robust CI/CD workflows.
  • Deploy models usingMLflow, SageMaker, or custom APIs.
  • Monitor production models for accuracy, drift, and latency; manage retraining schedules.

Data Integration & Architecture Alignment
  • Work closely with Data Engineering to align ML pipelines with the Bronze, Silver, Gold layers of a Medallion Architecture.
  • Engineer high-quality features and maintain training/inference pipelines.

Cloud and Platform Engineering
  • Leverage AWS services including S3, EC2, Lambda, SageMaker, and Step Functions.

Collaboration & Documentation
  • Document ML artifacts, processes, and performance outcomes.
  • Contribute to agile project ceremonies and maintain a feedback loop with stakeholders.
  • Share knowledge and mentor junior team members.

Required Skills:
  • 5+ years of experience in ML Engineering or Applied Machine Learning.
  • Strong Python skills and hands-on experience with ML libraries (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow).
  • Proficient with Databricks, MLflow, and PySpark.
  • Solid understanding of model lifecycle and MLOps practices.
  • Experience with AWS-based data infrastructure and related DevOps practices.
  • Demonstrated ability to productionize models and integrate with business system
  • Strong understanding of mathematics and statistics relevant to machine learning and AI.
  • Proven experience with machine learning models and algorithms (supervised, unsupervised, deep learning, etc.).
  • Solid background in software engineering principles and best practices.
  • Hands-on experience with model training frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Experience with MLOps tools and workflows, particularly on AWS (SageMaker, Lambda, S3, etc.).
  • Practical experience with LLMs, RAGs, and AI agent architectures.
  • Proficiency with the Databricks platform for data engineering and ML pipelines.
  • Advanced programming skills in Python.
  • Excellent communication and teamwork abilities.

Preferred Skills:
  • Experience building and deploying interactive UIs for AI models using Streamlit, Gradio, or similar frameworks for rapid prototyping and real-time model interactions
  • Business acumen and ability to align AI solutions with organizational goals.
  • Optimize compute and storage resources for performance and cost-efficiency.

Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Halvik Corp is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status.
Halvik's pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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