Qualified Applicants Opportunities Jobs in San Francisco, CA

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

Engineering Program Manager, Central Quality, Apple Services Engineering

Company: Apple

Location: San Diego, CA

Posted Aug 17, 2025

You will be responsible for synthesizing business and technical challenges and competing priorities across client, services, and operating systems engineering…

Security Officer - Armed Full Time

Company: Allied Universal

Location: San Antonio, TX

Posted Aug 18, 2025

A valid driver's license is required and must meet Allied Universal driver policy requirements for driving positions only. Must be at least 21 years of age.

Cellular Data Science & Machine Learning Engineer

Company: Apple

Location: San Diego, CA

Posted Aug 17, 2025

In addition, you will be closely partnering with FW engineering teams in integrating and deploying ML models and data processing pipeline as part of entire…

Unarmed Security Guard

Company: 1St Street Bar

Location: Encinitas, CA

Posted Aug 17, 2025

Greet guests and provide a welcoming presence at the door. Requirements:* Must be *21+* and hold a *valid California Guard Card*.

Apple Card Marketing Manager

Company: Apple

Location: Cupertino, CA

Posted Aug 17, 2025

You will be a key player on the Apple Card marketing team, responsible for driving business results through forecasting, test design, creative, segmentation,…

Armed Security Officer - Retail Patrol

Company: Allied Universal

Location: San Antonio, TX

Posted Aug 18, 2025

A valid driver's license is required for driving positions and must meet Allied Universal Driver Policy requirements. Must be at least 21 years of age.

Sr Software Engineer - Unreal (Interactive XR)

Company: The Walt Disney Studios

Location: Burbank, CA

Posted Aug 18, 2025

You will own the technical direction and optimize stakeholder satisfaction for a collection of internally developed products in addition to architecting and…

Part-Time Private Chef

Company: MAHLER PRIVATE STAFFING

Location: Manhattan Beach, CA

Posted Aug 17, 2025

A passionate chef with a strong background in clean, healthy, farm to table food. Willing to collaborate on grocery planning and kitchen inventory.

Frequently Asked Questions

What are the typical salary ranges for Qualified Applicants Opportunities by seniority?
Entry‑level AI/ML roles usually pay between $90,000 and $120,000 annually. Mid‑level positions range from $120,000 to $160,000, while senior roles can command $160,000 to $200,000. Lead or manager positions often exceed $200,000, reaching up to $250,000 in high‑cost‑of‑living markets or for highly specialized expertise.
What skills and certifications are required for these positions?
Core technical skills include Python, R, SQL, and statistical libraries. Proficiency with TensorFlow, PyTorch, scikit‑learn, and cloud‑native AI services (AWS SageMaker, Azure ML, GCP AI Platform) is essential. Certifications such as TensorFlow Developer, AWS Certified Machine Learning – Specialty, GCP Professional Data Engineer, and Kaggle Distinction demonstrate mastery and are highly valued.
Is remote work available for Qualified Applicants Opportunities?
Yes, approximately 80% of listings list remote or hybrid arrangements. Remote teams rely on tools like Slack, GitHub, MLflow, and cloud notebooks (Colab, SageMaker Studio) to collaborate across time zones while maintaining code quality and version control.
What career progression paths exist in this field?
Typical progression starts with a Data Analyst or Junior Data Scientist, advancing to Senior Data Scientist or ML Engineer. From there, professionals can move into Lead ML Engineer, AI Architect, or Director of AI/ML, often taking on strategic product direction and cross‑functional leadership responsibilities.
What industry trends are shaping Qualified Applicants Opportunities?
Key trends include the rise of edge AI for IoT devices, federated learning for privacy‑preserving models, increased focus on AI ethics and explainability, and the rapid deployment of AI in healthcare diagnostics and drug discovery. Companies are also investing in automated ML pipelines and no‑code AI platforms to democratize model development.

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