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Deep Learning Developer Jobs in New York (NOW HIRING)

Rebar

Senior Deep Learning Engineer

New York, NY · On-site

$114K - $157K/yr

We're looking for a Senior Deep Learning Engineer with extensive experience in modern neural network techniques and PyTorch to help us push the boundaries of computer vision in real-world ...

NBCUniversal

Deep Learning Engineer

Manhattan, NY · On-site

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision ...

NBCUniversal

Deep Learning Engineer

Manhattan, NY

$160K - $175K/yr

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision ...

NBCUniversal

Deep Learning Engineer

Manhattan, NY

We are seeking a Deep Learning Engineer with experience manipulating large 2D and 3D media datasets. In this role, you will implement core algorithms that sit at the intersection of computer vision ...

Rebar

Senior Deep Learning Engineer

Manhattan, NY

$115K - $158K/yr

We're looking for a Senior Deep Learning Engineer with extensive experience in modern neural network techniques and PyTorch to help us push the boundaries of computer vision in real-world ...

Seven Research

Deep Learning Researcher

New York, NY · On-site

$200K - $300K/yr

Your Role Our Deep Learning Researchers expand the boundaries of quantitative finance through the ... Strong programming skills, including mastery of Python * Strong problem-solving skills and research ...

Autodesk

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/yr

Train, adapt, and improve machine learning models, including classical ML models, deep learning ... Work closely with engineers, MLOps, and product partners to deploy, monitor, and iterate on ML ...

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Successful candidates will also have deep interest in learning about trading and the financial ... Researchers and developers there are passionate about their work, model building, data and ...

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 ...

HeyMilo AI

Machine Learning Engineer

Manhattan, NY

... deep learning, and reinforcement learning - Experience with data preprocessing and feature engineering techniques - Strong problem-solving skills and ability to think creatively to come up with ...

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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.

Senior Deep Learning Engineer

Rebar

New York, NY • On-site

$114K - $157K/yr

Full-time

Medical, Dental, Vision

Posted 3 days ago

Job description

Background
Rebar is building the next-generation operating system for commercial HVAC, electrical, and plumbing suppliers and subcontractors. Over the past year, our V1 quoting product has scaled to thousands of quotes completed weekly, doubled revenue in 2026, and gained adoption across many of the top suppliers in North America. Fresh off a $14M Series A backed by leading construction tech investors, we're entering our next phase of growth - with AI at the center of everything we build next.
We're looking for a Senior Deep Learning Engineer with extensive experience in modern neural network techniques and PyTorch to help us push the boundaries of computer vision in real-world environments. You'll be joining a small, highly capable team focused on delivering practical, production-ready ML systems - from data pipelines through to fine-tuned models - in a fast-moving startup context.
This role is ideal for someone who enjoys working with models under the hood, building and adapting training workflows, and applying research ideas to novel engineering challenges. Our work involves more than model inference - we design training workflows, develop evaluation pipelines, and engineer solutions that go beyond standard model usage.
Responsibilities
  • Model Training & Development: Design and train deep learning models for layout analysis, OCR, object detection, image to graph, and other related tasks. In some cases, you'll extend or adapt existing architectures; in others, you'll help design custom approaches from the ground up.
  • Evaluation and Monitoring: Build robust metrics, monitor production model performance, and proactively identify failure modes and areas for improvement.
  • Collaboration and Integration: Work closely with the engineering team to integrate models into our product and infrastructure. Participate in architecture and roadmap decisions.
What We're Looking For
You should feel confident implementing training logic, experimenting with model internals, and debugging the kinds of real-world issues that arise when pushing ML into production.
We're seeking someone with deep learning mastery and enjoys turning ideas into working, production-ready systems. This role is a great fit if you enjoy getting deep into PyTorch, working across the full ML stack, and solving open-ended modeling problems.
Required Qualifications
  • Master's degree or PhD in Computer Science, Electrical Engineering, or other relevant field with main focus on deep learning.
  • Proven ability to implement and adapt techniques or architectures from academic or industry literature.
  • Proven track record tackling novel ML challenges in the field of Deep Learning.
  • 3+ years of experience developing and adapting model architectures with PyTorch.
  • 2+ years of experience with deep learning for computer vision applications, especially semantic segmentation or object detection.
  • 2+ years of experience with production-level code development and optimization.

Nice to Have
  • Experience with active learning setups
  • Applied experience with RLHF (Reinforcement Learning from Human Feedback)
  • Published research developing SOTA computer vision or (or other DL) models
  • Experience with deployment and monitoring pipelines for ML systems.
Compensation and Benefits
  • Salary: Competitive
  • Equity: Meaningful equity package, commensurate with experience
  • Benefits: Comprehensive medical, dental, and vision coverage
  • Perks: Free lunches and dinners provided

This is a salaried, onsite role located in New York City's beautiful Flatiron district, just minutes away from Madison Square Park and Union Square. Working onsite offers invaluable opportunities for real-time collaboration, creative problem-solving, and building strong connections within our talented and dynamic team. You'll be at the heart of our fast-paced operations, actively contributing to a culture that values engagement, growth, and teamwork.

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