Ai-Enhanced Technology Jobs in San Francisco, CA

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

Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training

Company: Annapurna Labs (U.S.) Inc.

Location: Cupertino, CA

Posted Apr 09, 2025

Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations.

Project Manager II (DSA/K-14)

Company: Vanir Construction Management, Inc.

Location: Los Angeles, CA

Posted Apr 08, 2025

Based on his/her direct observations of conditions in the field and familiar with all aspects of the design and construction process and supporting…

AI Software Engineer

Company: Gallatin

Location: El Segundo, CA

Posted Apr 08, 2025

Deep understanding of deep neural networks (DNNs), LLMs, over/underfitting, prompt engineering, and LLM security (jailbreaking risks and protections).

Lead Carpenter

Company: Cal State University (CSU) San Jose

Location: San Jose, CA

Posted Apr 07, 2025

Ability to inspect work performed by others to ensure adherence to requirements and industry practices Ability to ensure shop, equipment, and tools are properly…

CAM Operator

Company: Sanmina Corporation

Location: San Jose, CA

Posted Apr 09, 2025

The CAM Operator is responsible for reviewing customer supplied data and drawings, performing design rule checks and creation of manufacturing data, programs…

AI Engineer

Company: Capsule

Location: Los Angeles, CA

Posted Apr 08, 2025

In this role, you will work closely with our founders and product and engineering teams to design, implement, and deploy ML models that power new and improved…

Retail Sales Representative FT

Company: ACO-US

Location: San Jose, CA

Posted Apr 08, 2025

Possess a valid driver’s license and ability to drive a car for extended periods of time. This position includes product merchandising, new item placement,…

STAFF ENGINEER

Company: Frost Bank

Location: San Antonio, TX

Posted Apr 09, 2025

Excellent communication skills with the ability to clearly articulate technical strategies to both technical and non-technical stakeholders.

Frequently Asked Questions

What are typical salary ranges by seniority for AI-Enhanced Technology roles?
Entry‑level ML Engineer or Data Scientist: $90k–$110k. Mid‑level: $120k–$150k. Senior/Lead: $160k–$200k. Staff/Principal: $210k–$260k. Director/VP: $250k–$350k (base + bonus + equity). These ranges reflect U.S. market averages for cloud‑native AI positions.
Which skills and certifications are most valuable in AI-Enhanced Technology?
Core skills: Python, PyTorch/TensorFlow, Kubernetes, Docker, CI/CD, Airflow, MLflow, SageMaker, Vertex AI, Azure ML, MLOps, reinforcement learning, generative models, NLP, CV, data engineering, SQL, Spark. Certifications: AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate, TensorFlow Developer Certificate, Certified Data Scientist (CDS), DeepLearning.AI TensorFlow Practitioner.
Is remote work common for AI-Enhanced Technology positions?
Yes. Many AI‑Enhanced Tech companies adopt remote‑first or hybrid models. Companies such as OpenAI, DeepMind, UiPath, NVIDIA, and Cloudflare offer fully remote roles; others provide 3‑4 days per week remote availability, while hardware‑lab positions may require occasional on‑site presence.
What career progression paths exist in AI-Enhanced Technology?
Typical trajectory: Junior Data Scientist → ML Engineer → MLOps Engineer → Lead ML Engineer → AI Solutions Architect → AI Product Manager → Director of AI → VP of AI. Each step adds responsibilities from model training to infrastructure management, product strategy, and executive leadership.
What are the current industry trends shaping AI-Enhanced Technology?
Key trends include generative AI and multimodal models, reinforcement learning for robotics, edge AI for IoT and autonomous vehicles, responsible AI and fairness regulation, AI‑Ops for continuous monitoring, AI‑as‑a‑Service platforms, and domain‑specific AI in healthcare diagnostics, finance fraud detection, and cybersecurity threat intelligence.

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