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.

Software Engineer Backend - Kohler Ventures

Company: Kohler

Location: Palo Alto, CA

Posted Jun 30, 2025

Bachelor's degree in CS/engineering or related technical discipline from a reputed academic institution. Work directly with the Head of Software, software…

Technical Project Lead - Proto Integrator

Company: ASML

Location: San Diego, CA

Posted Jun 30, 2025

Strong engineering, technical, and physics fundamentals. In this project management position you will have the opportunity to lead a team of dedicated EUV light…

Senior Staff Data Scientist

Company: Intuit

Location: San Diego, CA

Posted Jun 29, 2025

Contribute to and help refine a data science roadmap aimed at driving product funnel optimization and scalable growth initiatives.

Machinist (Manual)

Company: Joe's Industrial Machine Shop

Location: San Antonio, TX

Posted Jun 30, 2025

Must own tools of the trade, to include caliper (vernier). Understand the correct set-ups of tools to extend tool life and prevent damage to equipment.

Sr Staff Research Analyst (Vulnerability Research Team)

Company: Palo Alto Networks

Location: Santa Clara, CA

Posted Jun 30, 2025

Drive technical best practices and evangelize new technologies within the engineering organization. Take part in architecture strategy sessions; design…

Instructional Graphic Designer - Contract

Company: Alo Yoga

Location: Beverly Hills, CA

Posted Jun 30, 2025

This role sits within the Learning & Development team and is responsible for the design, development, and delivery of high-impact, visually compelling training…

Graphic Design Representative

Company: Child Development Associates

Location: Bonita, CA

Posted Jun 30, 2025

Minimum of three years’ professional experience in graphic design, marketing, or a related field. Provide graphic design and communication support to other CDA…

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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