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Tensorflow Pytorch Jobs in Puerto Rico (NOW HIRING)

Experience using Python, TensorFlow, PyTorch, OpenCV, or similar AI/ML frameworks. * Basic knowledge of statistical analysis using JMP, or other statistical software * Experience generating technical ...

PR · On-site

$99K - $117K/yr

Experience with computer vision and ML (PyTorch / TensorFlow, OpenCV). * Comfortable shipping models to production and the edge. * Strong Python and data-engineering skills; MLOps a plus. * Interest ...

Tensorflow Pytorch information

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 Puerto Rico? For Tensorflow Pytorch jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Tensorflow Pytorch jobs in Puerto Rico look for? The top searched job categories for Tensorflow Pytorch jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Tensorflow Pytorch jobs? Cities in Puerto Rico with the most Tensorflow Pytorch job openings:
Infographic showing various Tensorflow Pytorch job openings in Puerto Rico as of June 2026, with employment types broken down into 1% Internship, 90% Full Time, 7% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution.
Sr Data Scientist

Sr Data Scientist

BioPharma Consulting JAD Group

Juncos, PR • On-site

Contractor

Posted 12 days ago


Job description

The Sr. Data Scientist will lead advanced analytics initiatives and partner with cross‑functional teams—including Commercial Insights, Manufacturing, Supply Chain, Engineering, Data Teams, External Vendors, Service Owners, and IS partners—to design and implement analytical models that solve complex business challenges across the PR Operations Organization. This role is responsible for end‑to‑end project execution, from problem definition and methodology selection to model development, deployment, and communication of insights. The Sr. Data Scientist will drive innovation and deliver measurable business impact through strategic use of data science, machine learning, and artificial intelligence.

Key Responsibilities

  • Lead, develop, and apply data science, machine learning, and AI capabilities across operational and commercial functions.
  • Serve as project lead within cross‑functional teams to generate insights that deliver substantial business value.
  • Work independently with minimal supervision, proactively identifying analytical opportunities.
  • Conduct business needs assessments, perform SWOT analyses, propose analytical approaches, secure stakeholder alignment, and execute projects end‑to‑end.
  • Build high‑performance algorithms, prototypes, predictive models, and proof‑of‑concepts using Python.
  • Develop and execute SQL and other database queries across relational and graph databases.
  • Collaborate with stakeholders to define methodologies and analytical frameworks that address specific business questions.
  • Present analytical concepts, project updates, and results in a clear, compelling, and actionable manner.
  • Create strong data‑driven narratives and presentations using PowerPoint; demonstrate proficiency in Excel and the MS Office suite.
  • Ensure compliance with regulatory, security, and privacy requirements related to data assets.

Skills

  • Background in Data Science, Engineering, Mathematics, Applied Physics, Statistics, or Operations Research.
  • Proven experience leading and executing analytics projects end‑to‑end.
  • Strong experience with relational, SQL, and graph databases.
  • Programming proficiency in Python, R, or SAS; familiarity with ML libraries such as scikit‑learn, MLlib, Keras, TensorFlow, PyTorch, etc.
  • Ability to write well‑abstracted, reusable code; comfortable working in Linux environments.
  • Strong logical reasoning, problem‑solving, and decision‑making skills.
  • Excellent organizational skills and ability to manage large, complex datasets.
  • Ability to collaborate and influence cross‑functional partners to drive analytics initiatives.
  • Exceptional communication skills with the ability to translate complex analysis into clear, actionable insights.
  • Experience with distributed computing tools (Spark, Hive, etc.) and large‑scale data environments.
  • Passion for continuous learning and staying current with advanced analytics trends.
  • Experience in biotech or pharmaceutical environments preferred.

Requirements

Required Education & Experience

  • Doctorate OR
  • Master’s + 2 years of experience in data science, statistics, data mining, applied mathematics, business analytics, engineering, computer science, or related fields OR
  • Bachelor’s + 4 years of experience in related fields OR
  • Associate’s + 8 years of experience in related fields OR
  • High School/GED + 10 years of experience in related fields

Highly Preferred:

  • Degree in Computer Engineering or Computer Science
  • Specialized courses or certifications in Artificial Intelligence / Machine Learning

Preferred Qualifications

  • Experience supporting manufacturing operations; vial filling experience highly preferred.
  • Experience deploying or integrating AI solutions into manufacturing or operational environments.
  • Strong foundation in artificial intelligence, software development, and digital technologies.
  • Hands‑on experience developing AI/ML models for process optimization or task automation.
  • Knowledge of Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs).
  • Experience with Python, TensorFlow, PyTorch, OpenCV, or similar AI/ML frameworks.
  • Basic statistical analysis skills using JMP or similar tools.
  • Experience generating technical documentation, protocols, reports, and development records.
  • Knowledge of Good Documentation Practices (GDP), quality systems, and compliance requirements.
  • Strong project management and problem‑solving capabilities.
  • Ability to communicate effectively with both technical and non‑technical stakeholders.
  • Quality‑focused mindset with strong attention to detail.
  • High digital literacy and proficiency with AI tools and modern technologies.

Benefits

  • 5-month contract with possible extension
  • Administrative Shift