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Deep Learning Developer Jobs in New York (NOW HIRING)

Evolve Group

Machine Learning Researcher

Manhattan, NY · On-site

... deep learning models in PyTorch, JAX, or TensorFlow * Experience working with large-scale, computationally intensive datasets Bonus points JAX ecosystem (XLA, Flax) · GPU programming (CUDA, Triton ...

Clearview AI

Senior Machine Learning Engineer

Manhattan, NY · On-site

$115K - $158K/yr

Strong experience using PyTorch, JAX, or other deep learning frameworks to develop and optimize models * Strong software engineering ability to build and maintain complex systems and work with large ...

PhysicsX

Machine Learning Engineer

New York, NY · On-site

About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated ... Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ...

Orita

Senior Machine Learning Engineer

New York, NY · On-site +1

$180K - $250K/yr

Deep knowledge of modern machine learning algorithms (tree-based methods, deep learning ... Feature engineering using aggregations, embeddings, and sub-models. * MLOps & Cloud : * Track ...

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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.

AI Platform Developer

Qube Research & Technologies

New York, NY • On-site

$180K - $300K/yr

Full-time

Posted 8 days ago

Job description

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT's collaborative mindset which enables us to solve the most complex challenges. QRT's culture of innovation continuously drives our ambition to deliver high quality returns for our investors.
You'll help build and operate QRT's internal AI platform, enabling researchers, developers and data scientists to leverage LLM-powered tools effectively at scale. Working alongside experienced Platform Engineers, you'll contribute to production AI services including RAG pipelines, agentic workflows, retrieval infrastructure and internal APIs. This role is ideal for an early-career engineer or recent graduate with a strong foundation in AI and machine learning who is excited to bring cutting-edge models into production systems.
Your Future Role within QRT:
AI Platform Development -
  • Build and enhance internal AI services, APIs and production applications.
  • Contribute to RAG pipelines, including document ingestion, embeddings and retrieval.
  • Support the deployment of transformer-based models and agentic workflows.
  • Design scalable, well-documented APIs for internal users.
Platform Reliability & Quality -
  • Improve service reliability, latency and evaluation frameworks.
  • Contribute to prompt management, testing and human-in-the-loop controls.
  • Build resilient AI systems with monitoring and fallback mechanisms.
Operations & Observability -
  • Implement monitoring, tracing and quality metrics across AI services.
  • Support deployment, versioning and lifecycle management.
  • Participate in operational support and incident response alongside senior engineers.
Your Present Skillset:
We value a combination of academic achievement, research and practical experience. We do not expect candidates to meet every requirement below.
  • Bachelor's, Master's or PhD in Computer Science, Machine Learning, Engineering, Mathematics or another quantitative field, or equivalent practical experience.
  • Strong foundation in AI and machine learning, including exposure to transformers and reinforcement learning.
  • Strong Python skills and an interest in building production-grade software.
  • Experience with PyTorch or another deep learning framework.
  • Understanding of LLM fundamentals, including prompting, context management and model limitations.
  • Experience building AI/ML applications or working with LLMs or other deep learning models.
  • Exposure to cloud platforms (e.g. AWS) and modern software engineering practices.
  • Strong communication skills and the ability to collaborate across technical and non-technical teams.
Nice to Have:
  • Experience deploying ML or LLM models into production.
  • Familiarity with RAG systems, vector databases and retrieval techniques.
  • Experience with agentic AI systems, workflow orchestration or LLM evaluation.
  • Understanding of embeddings, retrieval performance and human-in-the-loop systems.
  • Experience building APIs, data pipelines or observability tooling.
  • Contributions to open-source projects, research publications or ML competitions (e.g. Kaggle).

Base salary range for this position is $180,000 to $300,000 per year.
QRT Total Compensation includes discretionary performance-based bonuses and a competitive benefits package.

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