Ai-Enhanced Technology Jobs in New York City, NY

759,351 open positions · Updated daily

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.

Store Associate

Company: CVS Health

Location: Auburn, NY

Posted Jan 25, 2025

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Store Associate

Company: CVS Health

Location: New Bedford, MA

Posted Jan 25, 2025

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Product Line Value Stream Senior Manager (Onsite)

Company: RTX

Location: Rome, NY

Posted Jan 25, 2025

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Shift Supervisor Trainee

Company: CVS Health

Location: New Kensington, PA

Posted Jan 25, 2025

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Sr. Associate, Workplace Site Operations

Company: Capital One

Location: Mexico City, Mexico

Posted Jan 25, 2025

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Relationship Banker - Smithaven Branch - Long Island, NY

Company: JPMorgan Chase

Location: Long Island, NY

Posted Jan 25, 2025

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Beauty Sales Consultant

Company: CVS Health

Location: New Canaan, CT

Posted Jan 25, 2025

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Pharmacy Technician

Company: CVS Health

Location: Queens, NY

Posted Jan 25, 2025

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Store Associate

Company: CVS Health

Location: Brooklyn, NY

Posted Jan 25, 2025

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Senior Manager, Product Management

Company: Capital One

Location: Mexico City, Mexico

Posted Jan 25, 2025

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Software Engineer, Early Career

Company: Google

Location: Mexico City, Mexico

Posted Jan 25, 2025

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transform lives with modern diagnostic driven care setting a new standard of people focused diagnostic driven care national clinical network of hundreds of physicians

Product Management Director

Company: Everly Health

Location: New York City, NY

Posted Jan 25, 2025

Everly Health, headquartered in Austin, Texas, is a leading company in diagnostic-driven healthcare. They aim to revolutionize healthcare by meeting people where they are, offering a range of services including telehealth test kits and AI-based care paradigms. The company is seeking a Product Management Director to lead and manage their Everlywell consumer products, requiring a strong track record in product management, deep understanding of the healthcare industry, and a passion for developing innovative healthcare products. The role involves leading the Everlywell Consumer products team, developing product strategies, and ensuring customer obsession in product development.

View Details Apply on BuiltIn

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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