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Remote Spacex Machine Learning Jobs in Fremont, CA

Unitytech

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Unitytech

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ... Mountain View, SF/Bay: $117,000 - $152,000 gross USD Bellevue, Seattle, NYC, Remote CA: $104,100 ...

Canals

Machine Learning Engineer

San Francisco, CA · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining ... We're remote-first, flexible, and distributed across North and South America, bringing together ...

Freenome

Senior Machine Learning Engineer

Brisbane, CA · On-site +1

$147K - $194K/yr

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine ... remote. What you'll do: * Implement and refine DL pipelines on distributed computing platforms ...

Freenome

Staff Machine Learning Scientist

Brisbane, CA · On-site +1

$199K - $283K/yr

... remote. What you'll do: * Independently pursue cutting edge research in AI applied to biological ... machine learning, deep learning and complex data modeling. * Practical and theoretical ...

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All JobsSpacex Machine Learning JobsRemote Spacex Machine Learning JobsRemote Spacex Machine Learning Jobs in Fremont, CA

Remote Spacex Machine Learning information

See Fremont, CA salary details

$27.9K

$46.6K

$96.3K

How much do remote spacex machine learning jobs pay per year?

As of Aug 12, 2026, the average yearly pay for remote spacex machine learning in Fremont, CA is $46,615.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,600.00 and $50,400.00 per year, depending on experience, location, and employer.

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?

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 popular job titles related to Remote Spacex Machine Learning jobs in Fremont, CA? For Remote Spacex Machine Learning jobs in Fremont, CA, the most frequently searched job titles are:
What job categories do people searching Remote Spacex Machine Learning jobs in Fremont, CA look for? The top searched job categories for Remote Spacex Machine Learning jobs in Fremont, CA are:
What cities near Fremont, CA are hiring for Remote Spacex Machine Learning jobs? Cities near Fremont, CA with the most Remote Spacex Machine Learning job openings:
Remote Spacex Machine Learning jobs near you

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Re-posted 14 days ago

Job description

Our client is a leader in healthcare innovation, seamlessly integrating pharmaceutical development, diagnostic solutions, and advanced technology and data capabilities.
Title: Machine Learning Engineer (Contract)
Pay rate: $55-73/hr+ (Depends on experience)
Location: Remote in the US or Canada, or onsite in SSF. Must be available during PST hours.
Duration: Through Dec. 2026 (Likely to get extended)
Overview:
Seeking a Machine Learning Bioinformatics Engineer to develop and deploy advanced ML solutions supporting pharmaceutical R&D. This role focuses on analyzing large-scale, multimodal clinicogenomic datasets (genomic, transcriptomic, clinical, and real-world data) to drive insights into disease biology, patient stratification, and treatment response. Ideal candidates are strong in both machine learning and bioinformatics, with a passion for translating complex data into impactful discoveries.
Key Responsibilities:
  • Build and deploy scalable, production-ready machine learning models
  • Process and analyze genomic and transcriptomic data using bioinformatics pipelines
  • Prepare high-quality, normalized biological datasets for downstream analysis
  • Train large-scale models using frameworks like PyTorch Lightning and Hugging Face
  • Develop cloud-based ML solutions (AWS/GCP) with a focus on scalability and reproducibility
  • Collaborate with cross-functional teams to uncover biomarkers and therapeutic targets
  • Provide technical input and guidance on ML system design and implementation

Qualifications:
  • PhD with 0-2 years of relevant work experience, or MS with 3-5 years of relevant work experience, or BS with 4-7 years of relevant work experience.
  • Proficient programming skills: Strong Python programming skills with extensive experience in ML and data libraries (e.g., NumPy, pandas, PyTorch).
  • Deep ML expertise: Excellent knowledge of modern machine learning methods and development best practices, including training strategies, model validation, performance visualization, and experimental design.
  • Deep bioinformatic expertise: Proficient knowledge of bioinformatic processing pipelines for genomic and transcriptomic variables.
  • Strong knowledge of computational oncology, cancer genomics and analysis of clinicogenomics datasets.
  • Must be authorized to work in the United States

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