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Remote Mechanical Engineering Machine Learning Jobs in California

Swish Analytics

Machine Learning Engineer

San Francisco, CA · On-site +1

$160K/yr

The Data Science team is hiring an experienced Machine Learning Engineer with a background building ... Engineering & Infrastructure Role Data Science Infrastructure Locations San Francisco, CA - Remote ...

Wings of Destiny

Machine Learning Engineer

Malibu, CA · On-site

Remote Commitment: 5-10 hours per week (flexible) Duration: 3-6 months (with potential extension ... Role Overview We are seeking a Machine Learning Engineer (Volunteer) to help design, build, and ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

We are building an AI-driven simulation software stack for engineering and manufacturing across ... We have hybrid offices in London, New York, and Singapore; this role is remote based in the San ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site +1

You are someone who can grasp advanced engineering concepts across multiple industries, and excel ... We have hybrid offices in London, New York, and Singapore; this role is remote based in the San ...

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

You will bridge the gap between core AI research and production-grade engineering, developing ... Employee divides their time between in-office and remote work. Access to an office location is ...

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

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Remote Mechanical Engineering Machine Learning information

Can mechanical engineers work in machine learning?

Mechanical engineers can work in machine learning by applying their knowledge of systems, modeling, and data analysis to develop algorithms for automation, robotics, or predictive maintenance. Gaining skills in programming languages like Python, and understanding of machine learning frameworks, can facilitate their transition into this field.

What is the difference between Remote Mechanical Engineering Machine Learning vs Remote Mechanical Engineering?

AspectRemote Mechanical EngineeringRemote Mechanical Engineering Machine Learning
Required CredentialsBachelor's or Master's in Mechanical EngineeringBachelor's or Master's in Mechanical Engineering; knowledge of Machine Learning
Work EnvironmentDesign, analysis, CAD modeling, testingDesign, analysis, CAD modeling with ML integration, data analysis
Industry UsageManufacturing, automotive, aerospaceManufacturing, automotive, aerospace with AI/ML applications
Common Search/ComparisonYesYes

Remote Mechanical Engineering involves traditional engineering tasks like design and analysis, while Remote Mechanical Engineering Machine Learning combines these with AI techniques to optimize processes and develop intelligent systems. The latter requires additional knowledge of machine learning but shares many core skills and industry applications.

What is a Remote Mechanical Engineering Machine Learning job?

A Remote Mechanical Engineering Machine Learning job combines mechanical engineering expertise with machine learning techniques, allowing professionals to develop intelligent systems and optimize mechanical processes from a remote location. These roles often involve tasks such as analyzing engineering data, building predictive models, automating design tasks, and enhancing product performance using AI algorithms. Working remotely, engineers collaborate with teams through digital platforms, contributing to research, development, and deployment of machine learning solutions in mechanical engineering applications.

Can I work remotely as a machine learning engineer?

Yes, many machine learning engineers, including those in mechanical engineering applications, can work remotely. Remote work is common in tech roles that involve programming, data analysis, and model development, often requiring skills in Python, TensorFlow, or similar tools. However, some positions may require on-site collaboration or access to specialized equipment, depending on the company's policies and project needs.

Which 5 jobs will survive AI?

Remote Mechanical Engineering roles that involve complex problem-solving, design, and hands-on work are likely to persist despite AI advancements. Jobs requiring creativity, critical thinking, and specialized expertise—such as research engineers, systems designers, and technical consultants—are less susceptible to automation. Continuous learning and proficiency with engineering tools and software can also enhance job security in this field.

What are some typical challenges faced by remote mechanical engineers working with machine learning, and how can they be managed?

Remote mechanical engineers who work with machine learning often face challenges such as effective cross-functional collaboration, accessing and sharing large datasets, and keeping communication clear across distributed teams. To manage these, it's important to leverage collaborative tools for version control, data management, and regular virtual meetings. Building strong communication habits and proactively seeking feedback from data scientists, software engineers, and other stakeholders will help ensure project alignment and smooth workflows.

What engineers make $500,000?

Senior mechanical engineers with extensive experience, specialized skills in areas like automation or aerospace, and advanced certifications can reach or exceed a $500,000 annual salary, especially in high-demand industries or leadership roles. Achieving this level often requires years of expertise, advanced degrees, and working in high-paying sectors or companies.
What are the most commonly searched types of Mechanical Engineering Machine Learning jobs in California? The most popular types of Mechanical Engineering Machine Learning jobs in California are:
What are popular job titles related to Remote Mechanical Engineering Machine Learning jobs in California? For Remote Mechanical Engineering Machine Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Mechanical Engineering Machine Learning jobs in California look for? The top searched job categories for Remote Mechanical Engineering Machine Learning jobs in California are:
What cities in California are hiring for Remote Mechanical Engineering Machine Learning jobs? Cities in California with the most Remote Mechanical Engineering Machine Learning job openings:
Remote Mechanical Engineering Machine Learning jobs near you
Machine Learning Engineer (Remote)

Machine Learning Engineer (Remote)

Astrix Inc

South San Francisco, CA • On-site, Remote

$55 - $73/hr

Full-time

Posted 24 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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