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Deep Learning Developer Jobs in New York (NOW HIRING)

Point72

Machine Learning Engineer

New York, NY · On-site

Experience with deep neural networks and representation learning * Prior experience working in a ... Proficiency in programming languages such as Python and R * Experience with machine learning ...

Point72

Machine Learning Engineer

New York, NY

Experience with deep neural networks and representation learning * Prior experience working in a ... Proficiency in programming languages such as Python and R * Experience with machine learning ...

Optiver

Machine Learning Research Engineer

New York, NY

$224K/yr

Conducting innovative research on deep learning for price forecasting * Building scalable and ... Collaborating closely with researchers and other engineers * Developing an in-depth understanding ...

Optiver

Machine Learning Research Engineer

New York, NY · On-site

$200K/yr

Conduct innovative research on deep learning for price forecasting * Build scalable and robust ... Collaborate closely with researchers and other engineers * Develop an in-depth understanding of ...

Cisco

Principal Machine Learning Engineer

Brooklyn, NY · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... Preferred : • Deep NLP & Domain‑Adapted LLMs: Background in building and adapting large‑scale ...

New

Virtu Financial

Machine Learning Researcher

New York, NY · On-site

$200K - $300K/yr

You'll tackle complex problems without obvious solutions, taking ownership of our entire modeling ecosystem-from feature engineering and deep learning architecture design to training dynamics and ...

Averity

Staff Machine Learning Engineer

Manhattan, NY · On-site

$170K - $215K/yr

Staff Machine Learning Engineer - AI Products Location: Hybrid in NYC (Bryant Park Office) Salary ... and deep learning * Proven track record of building scalable AI platforms used by millions

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Deep Learning Developer information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior Deep Learning Developer or AI research lead, often involving advanced skills in machine learning frameworks, data modeling, and programming. Such roles usually require extensive experience, specialized knowledge, and may include responsibilities like developing innovative AI solutions or leading AI teams in tech companies or research institutions.

What are the key skills and qualifications needed to thrive as a Deep Learning Developer, and why are they important?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What are Deep Learning Developers?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

Which 3 jobs will survive AI?

Deep Learning Developers are likely to continue to be in demand as AI advances because they design and improve AI models, requiring specialized skills in programming, mathematics, and data analysis. Other roles expected to persist include AI ethics specialists and AI system trainers, as human oversight and ethical considerations remain essential. These jobs involve complex problem-solving and domain expertise that are difficult to fully automate.

What is the difference between Deep Learning Developer vs Machine Learning Engineer?

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges Deep Learning Developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.

What engineer makes $500,000 a year?

Highly experienced deep learning developers or AI engineers with specialized skills in neural networks, large-scale data processing, and advanced machine learning frameworks can earn $500,000 or more annually, especially in senior or leadership roles at major tech companies or startups. Such roles often require advanced degrees, extensive experience, and a strong track record of deploying impactful AI solutions.

What engineers make $300,000 a year?

Deep learning developers and AI engineers with extensive experience, advanced skills in machine learning frameworks, and strong domain expertise can earn $300,000 or more annually, especially in high-demand industries or senior roles. Compensation often includes base salary, bonuses, and stock options, particularly at leading tech companies or startups with significant funding.
What cities in New York are hiring for Deep Learning Developer jobs? Cities in New York with the most Deep Learning Developer job openings:
Deep Learning Developer jobs near you
Infographic showing various Deep Learning Developer job openings in New York as of July 2026, with employment types broken down into 74% Full Time, 24% Part Time, and 2% Contract. Highlights an 76% Physical, 2% Hybrid, and 22% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Point72

New York, NY • On-site

Full-time

Re-posted 5 days ago

Job description

About Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role/Responsibilities:
We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team.
This role will apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations, such as creating a production support AI agent that helps monitor production problems and suggest actions.
This role will also work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.
Requirements:
  • PhD or PhD candidate in machine learning, computer science or other AI related research fields
  • Experience with sequential modeling and time series forecasting using deep learning
  • Experience with deep neural networks and representation learning
  • Prior experience working in a data driven research environment
  • Experience with translating mathematical models and algorithms into code
  • Proficiency in programming languages such as Python and R
  • Experience with machine learning software libraries such as TensorFlow or PyTorch
  • Experience implementing Agent or Context engineering is strongly preferred
  • Experience with natural language processing technology is strongly preferred
  • Excellent analytical skills, with strong attention to detail
  • Collaborative mindset with strong independent research ability
  • Strong written and verbal communication skills
  • Commitment to the highest ethical standards

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