Machine Learning Jobs in New York City, NY

416,957 open positions · Updated daily

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

Registered Nurse

Company: DaVita

Location: Manhasset, NY

Posted Jan 24, 2025

View Details Apply on The Muse

Driver I - Schenectady

Company: Aramark

Location: Schenectady, NY

Posted Jan 24, 2025

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Teachers at Children's Beginnings

Company: KinderCare Learning Companies

Location: Syracuse, NY

Posted Jan 24, 2025

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Partnerships Account Manager

Company: PitchBook Data

Location: New York, NY

Posted Jan 24, 2025

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powering the future of the advertising ecosystem AI and automation to optimize investments and outcomes Senior Backend Software Engineer

Senior Backend Engineer - DevOps Focus

Company: Mediaocean

Location: New York City, NY

Posted Jan 24, 2025

Mediaocean is a leading company in the advertising ecosystem, powering impactful omnichannel marketing experiences with AI and automation. They are seeking a Senior Backend Software Engineer with extensive experience in Python, AWS, and containerization technologies. The role involves architecting and developing scalable backend systems, managing cloud infrastructure, problem-solving, mentoring junior engineers, and ensuring high code quality and performance. Mediaocean offers a competitive salary, comprehensive benefits, and a wellness-focused environment.

View Details Apply on BuiltIn

Territory Account Executive MM

Company: Salesforce

Location: Mexico City, Mexico

Posted Jan 24, 2025

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Specialist Security System linux /UNIX

Company: Kyndryl

Location: Mexico City, Mexico / Remote

Posted Jan 24, 2025

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(USA) Technician, General Facilities Maintenance

Company: Walmart

Location: Albany, NY

Posted Jan 24, 2025

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Manager I, Engineering - Metrics Control Plane

Company: Datadog

Location: New York, NY

Posted Jan 24, 2025

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Growth Marketing Manager, B2B, AI

Company: Meta

Location: New York, NY

Posted Jan 24, 2025

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Teachers at New Hudson KinderCare

Company: KinderCare Learning Companies

Location: New Hudson, MI

Posted Jan 24, 2025

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Senior Data Scientist

Company: TransUnion

Location: White Plains, NY

Posted Jan 24, 2025

View Details Apply on The Muse

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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