Ai-Enhanced Technology Jobs in New York City, NY

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Looking for Ai-Enhanced Technology jobs in New York City, NY? Browse our curated listings with transparent salary information to find the perfect Ai-Enhanced Technology position in the New York City, NY area.

Lead Data Governance Analyst

Company: Disney Entertainment and ESPN Product & Technology

Location: New York, NY

Posted Jul 02, 2025

Masters Degree in a related field, and/or related certification/s. Lead Business and Functional Data Working Groups to assess and document current-state…

IT DATA ANALYST

Company: Ariel Partners

Location: Brooklyn, NY

Posted Jul 01, 2025

Process Improvement: Assist in developing and implementing strategies for improving data analysis processes. Data Analysis & Reporting: Generate comprehensive…

Data Science Analyst III - Mount Sinai Health Partners

Company: Mount Sinai

Location: New York, NY

Posted Jul 02, 2025

Provides a high degree of technical support to data analytics functions as they relate to varied business units, and technical expertise on the selection,…

Field Project Manager

Company: Mason Technologies

Location: New York, NY

Posted Jul 01, 2025

You will be out in the field on various projects in the tri-state area overseeing progress. Former field technician experience of at least 5+ years required.

Applied AI Engineer

Company: Columbia University

Location: New York, NY

Posted Jul 01, 2025

Exceptional communication skills are essential, as the role requires translating complex technical concepts into clear, actionable insights for both technical…

Applied Researcher II

Company: Capital One

Location: New York, NY

Posted Jul 01, 2025

Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.

Applied Researcher II

Company: Capital One

Location: New York, NY

Posted Jul 01, 2025

Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.

Applied Researcher II

Company: Capital One

Location: New York, NY

Posted Jul 01, 2025

Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.

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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