2

No Experience Nvidia Machine Learning Jobs in New York

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build ... Experience with NVIDIA GPU programming and CUDA * Experience with distributed training frameworks ...

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build ... Experience with NVIDIA GPU programming and CUDA * Experience with distributed training frameworks ...

Master's degree in Computer Science, Engineering, Information Systems, or related field. * 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras ...

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

About the Position Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience. You ...

Proven experience as a Machine Learning Engineer or similar role * Understanding of data structures, data modelling and software architecture * Deep knowledge of math, probability, statistics and ...

Machine Learning Compiler

New York, NY · On-site

$140K - $211K/yr

Preferred Qualifications: • Master's degree in Computer Science, Engineering, Information Systems, or related field. • 1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow ...

Experience developing and deploying machine learning models in production environments. Strong experience with computer vision, image classification, object detection, deep learning, or related ...

Master's degree in Computer Science, Engineering, Information Systems, or related field.1+ year of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).1+ ...

REMOTE Machine Learning Engineer This project-based consulting role invites an experienced Machine Learning Engineer to apply advanced analytical, statistical, and software engineering expertise to ...

Minimum of 2 years of experience in a data science role. Proficiency in programming languages such as Python or R.. Strong understanding of machine learning techniques and algorithms. Preferred ...

Experience with sequential modeling and time series forecasting using deep learning * Experience ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

Experience with sequential modeling and time series forecasting using deep learning * Experience ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

REQUIREMENTS Requires a bachelor's degree in computer science, engineering, data science or machine learning plus 2 years of experience as a machine learning engineer. Must also possess: 2 years ...

next page

Showing results 1-20

No Experience Nvidia Machine Learning information

What is the difference between No Experience Nvidia Machine Learning vs Data Analyst?

AspectNo Experience Nvidia Machine LearningData Analyst
Required CredentialsBasic understanding of machine learning concepts, no certifications neededDegree in statistics, mathematics, or related field; certifications optional
Work EnvironmentTech companies, AI research labs, or startups focusing on AI/ML projectsBusiness, finance, healthcare, or marketing sectors analyzing data for insights
Employer & Industry UsageUsed in AI/ML development teams, often entry-level roles in tech industryUsed across various industries for data-driven decision making

While No Experience Nvidia Machine Learning roles focus on entry-level understanding of AI and machine learning with minimal credentials, Data Analyst positions emphasize data interpretation skills often requiring a degree. Both roles are prevalent in tech and business sectors, but they serve different functions: AI development versus data insights.

What are the most commonly searched types of Nvidia Machine Learning jobs in New York?

The most popular types of Nvidia Machine Learning jobs in New York are:

What job categories do people searching No Experience Nvidia Machine Learning jobs in New York look for?

The top searched job categories for No Experience Nvidia Machine Learning jobs in New York are:

What cities in New York are hiring for No Experience Nvidia Machine Learning jobs?

Cities in New York with the most No Experience Nvidia Machine Learning job openings:

Machine Learning Engineer (Junior)

Pangram

New York, NY • On-site

$135K - $150K/yr

Full-time

Posted 10 days ago


Job description

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build software to support the machine learning development cycle from data generation, to training models, to deployment and monitoring production machine learning systems in real customer environments.
At Pangram, ML engineers are highly involved in the research effort, are involved in publishing research, and regularly contribute ideas and innovations to the team. However, formal research experience is not necessary. This is an in-person role in our office in Downtown Brooklyn, NYC.
Responsibilities:
  • Build robust data pipelines that mine the Internet at scale and generate millions of synthetic text examples for training detection models
  • Manage distributed infrastructure for multi-GPU LLM training
  • Profiling and optimizing training and inference code
  • Deploy efficient inference pipelines for serving LLMs at scale

Requirements:
  • B.S. or M.S. in Computer Science or related areas
  • Practical experience with deep learning: internships, undergrad or masters' level research projects in an academic lab, Kaggle competitions, or interesting side projects
  • Strong programming skills in Python and modern ML frameworks
  • Excellent understanding of transformers and LLM fundamentals
  • Comfort working across research and engineering boundaries

Nice to have
  • Experience with NVIDIA GPU programming and CUDA
  • Experience with distributed training frameworks, such as DeepSpeed, FSDL, Ray
  • Experience with inference frameworks like vLLM
  • Experience with large-scale data processing (Spark, Beam) and orchestration (Airflow)
  • Experience with MLOps and experiment tracking
  • Experience with DevOps tools
  • Familiarity with cloud-based infrastructure (AWS/GCP)