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Tensorflow Pytorch Jobs in Ridgefield Park, NJ (NOW HIRING)

Experience with embedded systems and machine learning programing * platforms including TensorFlow, PyTorch etc Additional Information All your information will be kept confidential according to EEO ...

AI Engineer

Manhattan, NY · On-site

$120 - $160/hr

Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, or scikit-learn * Experience with NLP, computer vision, or generative AI is a strong plus * Familiarity with cloud platforms ...

... TensorFlow, PyTorch, or similar. • Hands-on experience with MLOps, including model training, validation, deployment, and ongoing monitoring. • Proven ability to integrate AI/ML models into ...

Strong proficiency in Python, R, SQL, and ML/DL frameworks (TensorFlow, PyTorch). Hands-on experience with LLMs, Generative AI, NLP, and MLOps tools. Expertise in time-series modeling, predictive ...

Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch). * Solid understanding of machine learning algorithms and data structures. * Ability to work with large datasets and cloud ...

... TensorFlow PyTorch XGBoost or equivalent Knowledge of data visualization and analytical storytelling Strong problem solving and communication skills Preferred Qualifications Experience with ...

Hands‑on familiarity with tools and frameworks such as TensorFlow, PyTorch, NVIDIA Enterprise Suite, NeMO, and NIMs. * Ability to communicate effectively with both technical teams and executive ...

Showing results 21-40

Tensorflow Pytorch information

See Ridgefield Park, NJ salary details

$40.2K

$131.7K

$210.9K

How much do tensorflow pytorch jobs pay per year?

As of Sep 7, 2026, the average yearly pay for tensorflow pytorch in Ridgefield Park, NJ is $131,718.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,700.00 and $146,000.00 per year, depending on experience, location, and employer.

What are TensorFlow and PyTorch?

TensorFlow and PyTorch are two of the most popular open-source deep learning frameworks used by researchers and developers to build, train, and deploy machine learning models. TensorFlow, developed by Google, offers robust support for production environments and has a large ecosystem. PyTorch, developed by Facebook, is known for its flexibility, ease of use, and dynamic computational graph, making it popular in academia and research. Both frameworks support a wide range of neural network architectures and are used extensively for tasks such as computer vision, natural language processing, and reinforcement learning.

What are the key skills and qualifications needed to thrive as a deep learning engineer specializing in TensorFlow and PyTorch?

To thrive as a Deep Learning Engineer with a focus on TensorFlow and PyTorch, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree. Proficiency in programming languages like Python, experience with TensorFlow and PyTorch frameworks, and familiarity with cloud platforms or GPU computing are essential. Analytical thinking, problem-solving, and effective communication are standout soft skills for collaborating with teams and interpreting model results. These skills are crucial for developing, deploying, and optimizing AI models that drive innovation and solve complex real-world problems.

How do TensorFlow/PyTorch engineers typically collaborate with data scientists and other team members in a production environment?

TensorFlow and PyTorch engineers often work closely with data scientists to transform experimental machine learning models into efficient, scalable production solutions. Collaboration involves frequent code reviews, shared development environments, and regular meetings to align model requirements with deployment constraints. Engineers also coordinate with DevOps teams to ensure smooth integration and monitoring of models in production. Strong communication skills and a willingness to iterate on solutions are essential for bridging the gap between research and real-world application.

What is the difference between Tensorflow Pytorch vs Data Scientist?

AspectTensorflow PytorchData Scientist
Required SkillsDeep learning frameworks, Python, machine learningData analysis, statistical skills, Python/R, machine learning
Work EnvironmentAI/ML development, research, software engineeringData analysis, reporting, business insights
Industry UsageAI/ML projects, research labs, tech companiesBusiness, finance, healthcare, tech

Tensorflow and Pytorch are deep learning frameworks used primarily by AI/ML developers, while Data Scientists utilize these tools for data analysis and modeling. Although their skill sets overlap, Tensorflow Pytorch focus on model development, whereas Data Scientists apply these models to derive insights and inform decisions.

What cities near Ridgefield Park, NJ are hiring for Tensorflow Pytorch jobs?

Cities near Ridgefield Park, NJ with the most Tensorflow Pytorch job openings:

Infographic showing various Tensorflow Pytorch job openings in Ridgefield Park, NJ as of August 2026, with employment types broken down into 1% Internship, 89% Full Time, 5% Part Time, and 5% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution, with an average salary of $131,718 per year, or $63.3 per hour.

Sr Data Scientist with AI(FT role- NO OPT/CPT)

Apetan Consulting llc

Parsippany, NJ • Remote

$80 - $150/hr

Contractor

Re-posted 16 days ago


Job description

Position: Sr Data Scientist with AI((NO OPT/CPT)
Location: NJ – Remote
Type – Full Time
Job Description-:

  • Data Collection & Cleaning
  • Gather structured/unstructured data from databases, APIs, or external sources, then clean and preprocess it for analysis.
  • Exploratory Data Analysis (EDA)
  • Identify patterns, trends, and anomalies using statistical techniques and visualization tools.
  • Model Development
  • Build and train machine learning or AI models (e.g., regression, classification, clustering, deep learning).
  • AI/ML Implementation
  • Apply techniques from Machine Learning and Artificial Intelligence to solve business problems like prediction, recommendation, or automation.
  • Feature Engineering
  • Transform raw data into meaningful features that improve model performance.
  • Model Evaluation & Optimization
  • Test models using metrics (accuracy, precision, recall, etc.) and improve them.
  • Deployment & MonitoringWork with engineers to deploy models into production and monitor performance over time.
  • Communication
  • Translate complex results into actionable insights for stakeholders using dashboards, reports, or presentations.

Key Skills Required

Technical Skills

Programming: Python, R, SQL

Libraries/Frameworks: TensorFlow, PyTorch, Scikit-learn

Data Visualization: Matplotlib, Seaborn, Power BI, Tableau

Big Data Tools: Spark, Hadoop

Knowledge of Statistics and Linear Algebra

AI-Specific Skills

Deep learning, NLP, computer vision

Understanding of neural networks and optimization techniques

Familiarity with model deployment (MLOps basics)

Education & Background

Bachelor’s or Master’s in fields like:

Computer Science

Data Science

Mathematics / Statistics

Engineering

Certifications or hands-on projects in AI/ML are highly valued.