Machine Learning Jobs in San Francisco, CA

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Looking for Machine Learning jobs in San Francisco, CA? Browse our curated listings with transparent salary information to find the perfect Machine Learning position in the San Francisco, CA area.

Senior Software Engineer – AI Platform

Company: General Motors

Location: Mountain View, CA

Posted May 17, 2025

Our core responsibilities include building and scaling core AI infrastructure and tools to enable rapid development, training, fine-tuning, evaluation, and…

Biometrics AI Solutions Engineer

Company: Qualcomm

Location: San Diego, CA

Posted May 16, 2025

Contributes to discussion of design reviews for subsystem development; defines design constraints for a specific project; identifies solutions to meet design…

Executive Sous Chef

Company: FAIRMONT

Location: San Diego, CA

Posted May 15, 2025

Ensure that sanitation standards as set forth by Fairmont Grand Del Mar, local, state, and federal regulations are in compliance as well as the cleanliness and…

Algorithms and AI Principal Engineer

Company: ASML

Location: San Jose, CA

Posted May 17, 2025

Ability to understand customer problems, define technical directions, and conduct independent research to provide high quality solutions within time and cost…

Lead Graphic Production Artist

Company: Hogarth Worldwide

Location: Sunnyvale, CA

Posted May 15, 2025

Identify and help implement opportunities for process, automation, design, file format, and technical improvements. Familiarity with CMS, image and eDAM.

Machinist - 2nd Shift

Company: PEAK Technical Services Inc.

Location: San Antonio, TX

Posted May 15, 2025

Trade or technical school training in machining or related field. Proficient with measuring tools and equipment, including micrometers, calipers, indicators,…

Graphic Production Artist

Company: Hogarth Worldwide

Location: Sunnyvale, CA

Posted May 18, 2025

Photoshop expertise, particularly setting up files for web production and adhering to graphic design standards. Support training of newer team members.

Lead Carpenter

Company: San Jose State University

Location: San Jose, CA

Posted May 16, 2025

The Shop reports up to a Facilities Project Supervisor who provides supervision and guidance. The Lead Carpenter, assigned to the Carpenter Shop within the…

Integrated Visual Designer

Company: ThoughtSpot

Location: Mountain View, CA

Posted May 16, 2025

Bonus: experience with motion design, and GenAI tools like Runway, Descript, or ElevenLabs. A strong portfolio showcasing digital campaigns, social media, and…

Frequently Asked Questions

What are typical salary ranges for ML roles at different seniority levels?
Junior ML Engineers earn $90k–$120k annually, mid‑level engineers $120k–$160k, senior engineers $160k–$220k, and lead or principal ML roles can reach $220k–$300k+. In large tech firms, the upper end can exceed $350k when including equity, while early‑stage startups may offer lower base but higher stock options.
What skills and certifications are required for ML positions?
Core expertise includes Python, Jupyter, TensorFlow, PyTorch, scikit‑learn, and SQL. MLOps proficiency with Docker, Kubernetes, and cloud services (AWS SageMaker, GCP AI Platform, Azure ML) is essential for production roles. Certifications such as TensorFlow Developer, AWS Certified Machine Learning – Specialty, and Google Cloud Professional Machine Learning Engineer can validate knowledge and accelerate hiring.
Are ML jobs available for remote work?
Yes, many ML positions are fully remote or hybrid. Companies like Scale AI, Databricks, and Cohere offer remote‑first policies. Remote work requires high‑speed internet, secure VPN access, and collaboration via tools like JupyterHub, Slack, and Asana, but it also expands the geographic talent pool.
What career progression paths exist in ML?
Typical paths start as ML Engineer or Data Scientist, advance to Senior ML Engineer, Lead Data Scientist, or Research Scientist, then transition into managerial roles such as ML Manager, Director of AI, or VP of Data & AI. Progression hinges on building a strong portfolio, publishing research, mentoring junior teammates, and mastering cross‑functional skills like product strategy and ethics.
What are current industry trends shaping ML careers?
Edge AI and federated learning are driving demand for on‑device models; AutoML platforms reduce time to deployment; responsible AI frameworks (e.g., IBM AI Fairness 360) shape compliance roles; reinforcement learning is expanding into robotics; and interpretability tools like SHAP and LIME are becoming standard in regulated sectors such as finance and healthcare.

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