"What types of companies hire Machine Learning Engineers in NYC?"

New York City's ML ecosystem is diverse. You'll find opportunities at major tech companies (Google, Meta), leading financial institutions (JPMorgan, Two Sigma), media and adtech firms (Bloomberg, Spotify), and a rapidly growing number of AI startups across various sectors.

"Is visa sponsorship common for Machine Learning Engineer roles in New York City?"

Yes, visa sponsorship, particularly H-1B and O-1, is common for ML Engineers in NYC, especially with larger tech and finance companies. Many employers are experienced in navigating the immigration process for highly skilled talent.

"How does an ML Engineer role in NYC differ from an Applied Scientist or MLOps role?"

In NYC, ML Engineer roles typically focus on deploying, scaling, and maintaining ML models in production. Applied Scientists often focus more on research and developing new algorithms, while MLOps roles concentrate on the infrastructure and tooling for ML lifecycles. Companies here tend to have clear distinctions.

"What skills are most in demand for ML Engineers in New York City?"

Strong Python proficiency is essential, often with deep experience in frameworks like PyTorch or TensorFlow. Beyond core ML, skills in MLOps, cloud platforms (AWS, GCP, Azure), Kubernetes, distributed systems, and specific domain knowledge (e.g., NLP for media, time series for fintech) are highly valued.

Machine Learning Engineer • New York City

Machine Learning Engineer Jobs in New York City

New York City is a prime destination for Machine Learning Engineers, offering a unique blend of opportunities across booming sectors like fintech, media, adtech, and deep tech AI startups. This city isn't just about finance anymore; it's a rapidly evolving AI hub where your skills in deploying and scaling ML models are highly sought after. You'll find yourself at the intersection of innovation and enterprise, contributing to products that impact millions globally. The demand here for engineers who can translate research into production-ready systems is robust and growing. Navigating the diverse landscape of NYC's ML roles requires a keen understanding of local market nuances, from compensation structures to specific industry focuses. Whether you're a junior talent looking to make your mark or a seasoned professional seeking the next big challenge, New York City provides an unparalleled environment for Machine Learning Engineers to thrive and build impactful careers.

The Market

New York City hiring landscape

The New York City ML market is thriving, characterized by high demand across both established tech giants and an aggressive wave of AI startups. Fintech, media, and adtech sectors are heavily investing in ML for fraud detection, algorithmic trading, risk management, content recommendation, and personalized advertising. Recent shifts include a greater emphasis on MLOps and production-ready systems, moving beyond research-only roles. Hiring temperature is warm, with companies actively seeking talent capable of shipping models. You'll find a strong ecosystem supporting innovative ML applications, making NYC a dynamic place to grow your career.

Demand

High demand

Competition

Moderately competitive

Hub for

fintech, media, adtech

Salary range

Quoted in USD · base + typical equity for New York City

Junior$120k – $175k

Mid$180k – $260k

Senior$270k – $400k

Salaries in New York City for Machine Learning Engineers typically refer to total compensation, including base salary, annual bonuses, and significant Restricted Stock Units (RSUs) or equity grants, especially at mid to senior levels in tech companies. Expect equity to form a substantial part of your compensation package, particularly in public companies or well-funded startups. Negotiate for total comp, not just base.

See full machine learning engineer salary breakdown for New York City

Where to apply

Top employers in New York City

Google (New York)

As a major engineering hub for Google outside of Silicon Valley, their NYC office has significant AI/ML teams working on Search, Ads, Cloud AI, and Waymo. You'll find opportunities spanning core ML research to large-scale infrastructure.

TensorFlow, JAX, Kubernetes, Distributed ML, Custom ASICs.

Meta (New York)

Meta's NYC office is a key site for AI research and product development, contributing to areas like Instagram's ranking algorithms, VR/AR applications, and core AI infrastructure. Expect work on large-scale social graph and content recommendation systems.

PyTorch, TorchServe, Spark, Caffe2, Distributed Systems.

JPMorgan Chase (New York)

A leader in fintech, JPMorgan leverages ML across its operations for fraud detection, algorithmic trading, risk management, and client analytics. Their data science and ML engineering teams are expanding rapidly, integrating AI into critical financial services.

Python, Java, Keras, TensorFlow, AWS, Financial ML Libraries.

Bloomberg (New York)

Bloomberg, headquartered in NYC, is a powerhouse for financial data and media. They employ ML Engineers for natural language processing on financial news, market prediction, search relevance, and data analytics products, serving a global client base.

Python, C++, NLP, Time Series Analysis, Custom ML Platforms.

Datadog (New York)

A cloud-scale monitoring and security platform based in NYC, Datadog uses ML to process vast amounts of telemetry data for anomaly detection, root cause analysis, and intelligent alerting. You'll be building scalable ML services for critical infrastructure.

Python, Go, Kubernetes, Kafka, TensorFlow, Distributed Tracing.

Etsy (New York)

Headquartered in Brooklyn, Etsy focuses on personalization, search, and recommendation systems for its unique marketplace. ML Engineers here work on improving buyer experience, seller tools, and discovery through cutting-edge algorithms applied to e-commerce data.

Python, Java, Spark, TensorFlow, PyTorch, Recommendation Systems.

Spotify (New York)

Spotify's NYC presence is significant for its R&D. ML Engineers contribute to core features like music recommendations, podcast personalization, and ad targeting. You'll be working with massive datasets to enhance user engagement and discovery.

Scala, Python, Spark, TensorFlow, Factorization Machines, Reinforcement Learning.

Two Sigma (New York)

A highly quantitative hedge fund based in NYC, Two Sigma is at the forefront of applying advanced ML techniques to financial markets. Their ML Engineers develop and deploy sophisticated models for trading strategies, risk assessment, and data analysis.

Python, C++, KDB+, Distributed Computing, Advanced Statistical Modeling.

Playbook

Apply smarter, not faster

Clarify Your Role Preference

Many NYC companies differentiate sharply between ML Engineers, MLOps Engineers, and Applied Scientists. Clearly articulate your preference and experience in your resume and cover letter to avoid being miscategorized during initial screening. This saves both you and the recruiter time and ensures you're considered for roles truly aligned with your skills.

Showcase Production Experience

Given NYC's focus on shipping, prioritize projects or experience where you've deployed ML models to production, managed their lifecycle, or optimized their performance in real-world systems. Highlight impact and scale. Hiring managers want to see that you can build and deliver, not just research.

Tailor to Industry Verticals

Research whether the company operates in fintech, adtech, media, or SaaS. Frame your experience to emphasize how your ML skills would apply to their specific industry challenges (e.g., fraud detection for banks, recommendation systems for media). Demonstrates commercial awareness and shows you've done your homework beyond generic ML applications.

Practice System Design with ML Focus

NYC interviews frequently include ML System Design rounds. Practice designing end-to-end ML systems, considering data pipelines, model training, serving infrastructure, monitoring, and scaling. Be ready to discuss trade-offs. This is a critical signal for your ability to contribute effectively in a production environment.

Be Prepared for Take-Home Assessments

Several companies in NYC utilize take-home challenges. Allocate dedicated time for these, as they often simulate real-world problems and can take a full weekend. Don't rush or submit incomplete work. A well-executed take-home can significantly boost your chances, demonstrating your problem-solving and coding prowess.

Network within NYC's AI Meetups

Attend local AI/ML meetups and conferences in New York City. Networking can uncover hidden opportunities, provide insights into company cultures, and help you understand the specific technical stacks favored by local employers. Personal connections can open doors that online applications alone might not.

Visa & relocation

Working in New York City

For international candidates, a visa is typically required to work as an ML Engineer in New York City. Strong H-1B and O-1 visa sponsorship is common across major tech firms and financial institutions. Many companies, especially larger ones like Google, Meta, and major banks, have established immigration teams to support the process. English is the sole language used in the workplace. Relocation packages, including flight, temporary housing, and moving expenses, are often provided by larger employers for senior or critical roles, but vary by company and seniority.

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