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Tensorflow Pytorch Jobs in Schenectady, NY (NOW HIRING)

ACS Consultancy Services

AI/ML Engineer

Albany, NY · Remote

Build and optimize data pipelines and ML workflows using frameworks like TensorFlow, PyTorch, scikit-learn, or XGBoost. * Implement models in production environments using MLOps best practices (e.g ...

Versant Health

Senior Data Scientist

Troy, NY · On-site

Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow where appropriate) * SQL (advanced T-SQL optimization, analytical patterns) * ML explainability and governance techniques (e.g., SHAP-style ...

Kitware

Machine Learning Engineer

Clifton Park, NY

$85K - $125K/yr

Experience with deep learning libraries (PyTorch, TensorFlow, etc.) * Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting ...

Kitware

Machine Learning Engineer

Clifton Park, NY

$85K - $125K/yr

Experience with deep learning libraries (PyTorch, TensorFlow, etc.) * Strong background in both classical and modern (deep learning) machine learning, including model selection, architecting ...

All JobsTensorflow Pytorch JobsTensorflow Pytorch Jobs in Schenectady, NY

Tensorflow Pytorch information

See Schenectady, NY salary details

$36.3K

$118.8K

$190.1K

How much do tensorflow pytorch jobs pay per year?

As of Jul 20, 2026, the average yearly pay for tensorflow pytorch in Schenectady, NY is $118,753.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,300.00 and $131,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Deep Learning Engineer specializing in TensorFlow and PyTorch, and why are they important?

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.

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 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.

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 are popular job titles related to Tensorflow Pytorch jobs in Schenectady, NY? For Tensorflow Pytorch jobs in Schenectady, NY, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Schenectady, NY look for? The top searched job categories for Tensorflow Pytorch jobs in Schenectady, NY are:
What cities near Schenectady, NY are hiring for Tensorflow Pytorch jobs? Cities near Schenectady, NY with the most Tensorflow Pytorch job openings:
Tensorflow Pytorch jobs near you

AI/ML Engineer

ACS Consultancy Services

Albany, NY • Remote

Other

Re-posted 26 days ago

Job description

Job Title: AI/ML Engineer

Location: Remote

We are currently seeking candidates who meet the following qualifications.

Key Responsibilities

  • Develop, train, and deploy machine learning and deep learning models for classification, prediction, recommendation, NLP, or computer vision tasks.
  • Work with large, structured and unstructured datasets to extract insights and prepare data for modeling.
  • Build and optimize data pipelines and ML workflows using frameworks like TensorFlow, PyTorch, scikit-learn, or XGBoost.
  • Implement models in production environments using MLOps best practices (e.g., model versioning, monitoring, CI/CD).
  • Collaborate with software engineers to integrate AI/ML solutions into production applications and services.
  • Perform model evaluation, A/B testing, and tuning to ensure high performance and reliability.
  • Stay current with the latest research and trends in machine learning and artificial intelligence.
Requirements
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
  • Experience in AI/ML engineering or a related role.
  • Proficient in Python and familiar with ML libraries such as TensorFlow, Keras, PyTorch, scikit-learn, and pandas.
  • Solid understanding of supervised, unsupervised, and deep learning algorithms.
  • Experience with cloud platforms (AWS, Azure, or GCP) and services like SageMaker, Vertex AI, or Azure ML.
  • Experience with version control (Git) and containerization tools like Docker and Kubernetes.
  • Strong problem-solving skills and a collaborative mindset.
  • Federal Experience is a plus.
  • Required Security clearance.
    If you meet these qualifications, please submit your application via link provided in Linkedin.
    Kindly do not call the general line to submit your application.