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.

Staff Software Engineer

Company: Intuit

Location: San Diego, CA

Posted Aug 09, 2025

Excellent communication and presentation skills: Demonstrated ability to explain complex issues to both technical and non-technical audiences.

Internal Communications Manager, Strategic Response

Company: Meta

Location: Menlo Park, CA

Posted Aug 09, 2025

7+ years of experience in internal or corporate communications, or a related field. Bachelor's degree in Communications, Public Relations, or a related field.

Accountant

Company: City of San Antonio

Location: San Antonio, TX

Posted Aug 09, 2025

Maintains and reconciles monthly reports, invoices, statements, and other records of financial transactions. Participates in the completion of special studies…

Game Engineer, Platform Architecture

Company: Apple

Location: San Diego, CA

Posted Aug 09, 2025

As Game Engineer on the Tools & Technology team, you will develop and maintain the bespoke engine, requiring architectural design, implementation, debugging and…

Executive Director, Data Scientist

Company: USAA

Location: San Antonio, TX

Posted Aug 09, 2025

Leverages state-of-the-art machine learning/AI tools and analytical methodologies to develop and implement various types of predictive models with the targeted…

Drain Installer

Company: Bill Howe Plumbing

Location: San Diego, CA

Posted Aug 09, 2025

Driver's License: Valid driver's license with a clean driving record. Perform pipe excavation, layout, and installation using industry-standard tools and…

RN, Registered Nurse - Postpartum

Company: Christus Health

Location: San Antonio, TX

Posted Aug 09, 2025

Current STABLE (Post-resuscitation/Pre-transport Stabilization Care of Sick Infants) certification required from one of the following courses: Participant, Lead…

GIS Solution Engineer - Natural Resources

Company: Esri

Location: San Antonio, TX

Posted Aug 10, 2025

Successfully design presentations for technical and non-technical customers. Bachelor's in geography, computer science, or a related field.

AI Engineer (12 months or 18 months fixed-term)

Company: Khan Academy

Location: Mountain View, CA

Posted Aug 09, 2025

2+ years of transferrable technical experience (e.g., software engineering, ML engineering, data science). Technical Proficiency: You have experience working in…

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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