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Deep Learning Developer Jobs in New York (NOW HIRING)

Optiver

Machine Learning Research Engineer

New York, NY

$224K/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 ...

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 ...

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 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 resilient roles include AI ethicists, who address ethical considerations, and AI system trainers, who curate and annotate data to improve AI performance. These jobs involve complex problem-solving and human oversight that are less easily automated.

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 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 June 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 89% Full Time, 2% Part Time, 3% Temporary, and 4% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.

Machine Learning Research Engineer

Optiver

New York, NY

$224K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago

Job description

Optiver is a seeking a Machine Learning Research Engineer to join our team, focusing on a pivotal AI initiative.  This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies.

What you'll do:

  • Conduct innovative research on deep learning for price forecasting 
  • Build scalable and robust training and inference pipelines for deep learning
  • Dive into internals of open-source deep learning frameworks and enhance their functionality
  • Collaborate closely with researchers and other engineers
  • Develop an in-depth understanding of trading systems

What you'll get:

You'll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you'll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets.

In addition, you'll receive:

  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • A highly competitive compensation package
  • Global profit-sharing pool and performance-based bonus structure
  • 401(k) match up to 50%
  • Comprehensive health, mental, dental, vision, disability, and life coverage
  • 25 paid vacation days alongside market holidays
  • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more

Who you are: 

  • PhD or equivalent industry experience in a field related to machine learning
  • Expertise in building deep-learning models in PyTorch, JAX, or TensorFlow
  • Experience in programming in Python
  • Experience in computationally intensive research on very large data sets

Nice to have:

  • Experience with JAX ecosystem (XLA, Flax, etc.)
  • Experience in programming for GPUs or other accelerators (CUDA, Triton, Pallas, etc.)
  • Contributions to open-source projects related to data science and machine learning
  • Strong publication record at conferences like NeurIPS, ICML, etc.
  • Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.
  • Experience with large-scale distributed training
  • Experience in programming in C++

Who we are:

Optiver is a tech-driven trading firm and leading global market maker. As one of the oldest market making institutions, we are a trusted partner of 70+ exchanges across the globe. Our mission is to constantly improve the market by injecting liquidity, providing accurate pricing, increasing transparency and acting as a stabilizing force no matter the market conditions. With a focus on continuous improvement, we participate in the safeguarding of healthy and efficient markets for everyone who participates.

Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.

ical or mental disability, or other legally protected characteristics.

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