ZipRecruiter

Log In

1

Data Scientist Deep Learning Jobs (NOW HIRING)

Vytwo

Data Scientist - INDIA

Prosper, TX · On-site

Data Science Structured Data / Text Data (NLP & GenAI) About the Role We are seeking a highly ... Text / Unstructured Data (NLP & GenAI) Building lowlatency realtime systems using deep learning ...

Sarian, Inc.

Sr. Data Scientist

Irving, TX · On-site

Role: Data Scientist Location: Irving, TX - Fulltime Position Data Scientist with Generative AI ... Machine learning, NLP & deep learning: Strong understanding of supervised and unsupervised learning ...

Inherent Technologies

Data Scientist

Chandler, AZ · Remote

Strong Time Series forecasting, ML, deep learning and standard statistical methods to evaluate models. Experience working on supply chain projects. We are seeking a highly skilled Data Scientist to ...

Tenex.AI Inc

Senior Data Scientist

San Jose, CA · On-site

Stay up-to-date on state-of-the-art research in data science, deep learning, and security-specific AI to drive platform innovation. * Explore novel statistical methods and machine learning techniques ...

Apex Informatics

AI Data Scientist

... on deep learning and LLM approaches • Stay abreast of leading-edge technologies in machine ... or data science: data analysis, algorithm design, model architecture specification, machine ...

Mindlance

Data Scientist

Holtsville, NY · On-site

Data Scientist Job Location: Holtsville, NY Duration: 6+ Months Responsibilities: - Design, build ... Technical Skills - Strong foundation in machine learning, deep learning, and AI frameworks ...

Augment

Principal Scientist, Data

Houston, TX

$80 - $83/hr

Data Scientist - AI/ML Focus Worksite: Onsite Monday-Thursday (Mandatory) - Houston, TX Must-Have ... Design, train, fine-tune, and evaluate machine learning and deep learning models--including LLMs ...

JS Consulting

Data Scientist

Washington, DC · On-site

Work or educational background in one or more of the following areas: machine learning, computational linguistics, deep learning, ratification intelligence, data science and/or data analytic ...

Agile Tech Labs

Data Scientist

Detroit, MI · On-site

Job Title: Data Scientist Job Location: Detroit, MI (Hybrid) Job Type: Contract * Develop and ... Strong experience with Machine Learning, Deep Learning, and NLP. * Proficiency in Python.

Raas Infotek LLC

Senior Data Scientist

Dallas, TX · On-site

Senior Data Scientist Location: Taxes Experience: 12+ Years Job Summary We are seeking an ... Expertise in Machine Learning , Deep Learning , and Statistical Modeling * Experience with ...

New

TechYantram Solutions

Data Scientist

Boston, MA · On-site

As a Data Scientist, you will be responsible for analyzing complex data sets to inform business ... Experience with TensorFlow or PyTorch for deep learning. * Understanding of MLOps for managing ...

next page

Showing results 1-20

All JobsData Scientist Deep Learning Jobs

Data Scientist Deep Learning information

See salary details

$37.5K

$122.7K

$196.5K

How much do data scientist deep learning jobs pay per year?

As of Jul 9, 2026, the average yearly pay for data scientist deep learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Scientist Deep Learning, and why are they important?

To excel as a Data Scientist specializing in Deep Learning, you need a strong background in mathematics, statistics, and programming (often Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, as well as experience in handling large datasets and cloud platforms, is essential, and certifications in machine learning can be advantageous. Analytical thinking, problem-solving, and effective communication are crucial soft skills for interpreting data results and collaborating with cross-functional teams. These skills and qualities are vital for building advanced AI models, deriving actionable insights, and driving innovation in data-driven organizations.

What is the difference between Data Scientist Deep Learning vs Data Scientist Machine Learning?

AspectData Scientist Deep LearningData Scientist Machine Learning
Required CredentialsBachelor's/Master's in CS, Data Science, or related; experience with neural networksBachelor's/Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch, AI-focused projects, neural network developmentData analysis, predictive modeling, algorithm development
Industry UsageAI, computer vision, NLP, speech recognitionFinance, marketing, healthcare, general analytics
Common Search/ComparisonYesYes

Data Scientist Deep Learning specializes in neural networks and AI-driven models, often working on complex tasks like image recognition and NLP. Data Scientist Machine Learning covers a broader range of algorithms and applications, including predictive analytics and traditional machine learning models. Both roles require strong programming skills and statistical knowledge, but Deep Learning roles focus more on neural network frameworks and AI-specific tools.

What are Data Scientist Deep Learning roles?

Data Scientist Deep Learning roles focus on designing, building, and implementing deep learning models to solve complex problems using large datasets. These professionals apply neural networks and advanced machine learning techniques to tasks such as image recognition, natural language processing, and predictive analytics. They work with programming languages like Python, use frameworks such as TensorFlow or PyTorch, and often collaborate with cross-functional teams to turn data insights into actionable solutions. Strong mathematical, statistical, and programming skills are essential for success in this role.

How do Data Scientist Deep Learning professionals typically collaborate with other teams in a tech organization?

Data Scientist Deep Learning professionals frequently work cross-functionally, partnering with data engineers to prepare and optimize data pipelines, collaborating with machine learning engineers to deploy and scale models, and communicating findings to product managers and stakeholders in accessible terms. This collaborative environment ensures that deep learning solutions are both technically robust and aligned with business goals. Regular meetings and agile workflows help facilitate smooth communication and integration of deep learning models into production systems.
More about Data Scientist Deep Learning jobs
What are the most commonly searched types of Data Scientist Deep Learning jobs? The most popular types of Data Scientist Deep Learning jobs are:
What job categories do people searching Data Scientist Deep Learning jobs look for? The top searched job categories for Data Scientist Deep Learning jobs are:
Data Scientist Deep Learning jobs near you
Infographic showing various Data Scientist Deep Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist - INDIA

Vytwo

Prosper, TX • On-site

Full-time

Posted 9 days ago

Job description

Role: Data Scientist - INDIA
Location: Hyderabad / Noida, INDIA
*Consultants local to INDIA are eligible.Category: Data Science Structured Data / Text Data (NLP & GenAI)
About the Role

We are seeking a highly skilled Data Scientist (37 years of experience) to join our team and work across two major data science domains:
  1. Structured Data (8090%) Predictive analytics, forecasting, cost estimation, likelihood modeling, and batchoriented machine learning pipelines.
  2. Text / Unstructured Data (NLP & GenAI) Building lowlatency realtime systems using deep learning, LLMs, prompt engineering, and agentic AI frameworks.
This role requires strong expertise in Big Data processing, modern ML tools, and the ability to build scalable, production-ready data science solutions.
Key Responsibilities

Structured Data Machine Learning & Analytics

  • Build, deploy, and optimize ML models for predictive analytics, forecasting, classification, and regression.
  • Perform large-scale feature engineering using PySpark and Big Data tools.
  • Work on batch pipelines, model versioning, and experiment tracking.
  • Develop cost estimation and risk/likelihood models using statistical and ML techniques.
Text Data / NLP / GenAI

  • Build NLP pipelines using deep learning frameworks such as PyTorch, TensorFlow, or similar.
  • Develop realtime, lowlatency inference systems for text classification, embeddings, semantic search, summarization, and retrieval.
  • Create prompts, context graphs, and agentic workflows for LLM-based systems.
  • Apply knowledge of prompt engineering, context engineering, and autonomous agent frameworks to production systems.
Core Data Science Engineering & MLOps

  • Work in Databricks for ETL, feature engineering, ML training, and orchestration.
  • Use Azure services for model deployment, data pipelines, and infrastructure.
  • Collaborate using Git-based workflows; leverage tools like GitHub Copilot, Claude Code, etc.
  • Implement model monitoring, observability, drift detection, and performance tracking.
Required Skills & Experience

Core Skills

  • Strong hands-on experience with Databricks (Delta Lake, MLflow, Job Orchestration).
  • Excellent PySpark skills for large-scale distributed data processing.
  • Proficiency in Azure cloud services (ADF, Azure ML, AKS, Databricks on Azure).
  • Strong understanding of ML algorithms, statistical methods, and data analysis.
  • Experience with deep learning frameworks:
    • PyTorch
    • TensorFlow
    • Transformers (HuggingFace)
  • Experience with model monitoring and ML observability.
  • Ability to write clean, optimized code and leverage AI code assistants.
NLP / GenAI Specific Skills

  • Prompt engineering (task prompts, chain of thought, tool calling, retrieval prompts).
  • Context engineering (retrieval pipelines, RAG, memory management, context structuring).
  • Knowledge of LLM-based agentic frameworks (LangChain, Semantic Kernel, CrewAI, AutoGen, etc.).
  • Experience with vector databases and embedding models is a plus.
Good to Have Skills

  • Experience with containerization (Docker, Kubernetes, AKS).
  • Experience deploying models to production (REST APIs, real-time endpoints).
  • Knowledge of streaming technologies (Kafka, EventHub, Spark Streaming).
  • Understanding of CI/CD for ML (Azure DevOps / GitHub Actions).
Who You Are

  • A problem solver who is comfortable working with both structured and unstructured data.
  • Someone who enjoys using modern AI tools to accelerate development.
  • A data scientist who writes clean, production-grade code.
  • A collaborator who thrives in cross-functional teams and fast-paced environments.

Flexible work from home options available.