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Lstm Model Jobs (NOW HIRING)

EchoStar

Senior Data Scientist

Littleton, CO · On-site

$141K/yr

Design and deploy time-series forecasting models using Prophet, ARIMA, and LSTM to predict weekly device sales and subscriber activations, enabling demand planning teams to reduce forecast variance.

Walmart

(USA)Staff, Data Scientist

Sunnyvale, CA · On-site

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

Walmart

(USA)Staff, Data Scientist

Fremont, CA

$143K - $286K/yr

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

Walmart

(USA)Staff, Data Scientist

San Jose, CA

$143K - $286K/yr

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

Adidev Technologies Inc

Data Science

San Francisco, CA · On-site

Strong skills in scientific data analyses, modeling, visualization and communication of results ... Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras * Machine ...

Adidev Technologies Inc

DATA SCIENTIST

Austin, TX · Remote

Strong skills in scientific data analyses, modeling, visualization and communication of results ... Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras * Machine ...

Adidev Technologies Inc

Data Science

San Francisco, CA · Remote

Strong skills in scientific data analyses, modeling, visualization and communication of results ... Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras * Machine ...

Walmart

(USA)Staff, Data Scientist

Cupertino, CA

$143K - $286K/yr

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

Walmart

(USA)Staff, Data Scientist

San Mateo, CA

$143K - $286K/yr

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

Walmart

(USA)Staff, Data Scientist

Hayward, CA

$143K - $286K/yr

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

Walmart

(USA)Staff, Data Scientist

Milpitas, CA

$143K - $286K/yr

ML approaches (GBMs, Random Forests, linear/elastic models with engineered time features) * Deep learning (RNN/LSTM/GRU, Temporal Convolutional Networks (TCNs), TimesFM) * Probabilistic forecasting ...

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Lstm Model information

What are the key skills and qualifications needed to thrive as an LSTM Model Developer, and why are they important?

To thrive as an LSTM Model Developer, you need a solid background in machine learning, deep learning, and programming, typically supported by a degree in computer science, data science, or a related field. Proficiency with Python, TensorFlow, Keras, and knowledge of time series data handling are crucial, as are relevant certifications in AI or deep learning. Strong analytical thinking, attention to detail, and effective problem-solving set exceptional candidates apart. These skills ensure the development of robust and accurate LSTM models for complex sequence prediction tasks and real-world applications.

What are some common challenges faced when deploying LSTM models in a production environment?

Deploying LSTM models in production often involves challenges such as managing computational resources due to the model's complexity and ensuring low-latency predictions for real-time applications. Additionally, LSTMs can be sensitive to input data format and require careful preprocessing and consistent data pipelines. Monitoring model performance over time is essential, as LSTMs may degrade if the underlying data distribution changes. Collaborating with data engineers and DevOps teams is also key to ensure smooth integration and scalability.

What is the difference between Lstm Model vs Data Scientist?

AspectLstm ModelData Scientist
Required CredentialsKnowledge of machine learning, deep learning, programming (Python, TensorFlow)Statistics, programming, data analysis, often a degree in related fields
Work EnvironmentDeveloping models, coding, testing algorithmsData analysis, reporting, collaborating with teams
Industry UsageAI, NLP, time-series forecastingBusiness analytics, research, data-driven decision making

While an Lstm Model is a specific deep learning technique used for sequence data, a Data Scientist applies various methods, including LSTM, to analyze data and generate insights. The LSTM model is a tool within a Data Scientist's skill set, focusing on model development, whereas Data Scientists handle broader data analysis tasks across industries.

What is an LSTM model?

An LSTM (Long Short-Term Memory) model is a type of recurrent neural network (RNN) architecture used in the field of deep learning. It is specifically designed to learn and remember long-term dependencies in sequential data, making it highly effective for tasks like language modeling, speech recognition, and time series prediction. LSTM models use special memory cells and gating mechanisms to manage and update information over long sequences, which helps them overcome the limitations of traditional RNNs such as the vanishing gradient problem.
Infographic showing various Lstm Model job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 84% Full Time, 14% Part Time, and 1% Temporary. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.
Mid-Level AI / Machine Learning Software Engineer

Mid-Level AI / Machine Learning Software Engineer

Modern Technology Solutions, Inc.

Huntsville, AL • On-site

$112K - $135K/yr

Full-time

Posted 14 days ago

Job description

We are seeking a Mid-Level AI / Machine Learning Software Engineer to support development of scalable data analysis and machine learning capabilities across large datasets and real-time data streams. The role focuses on designing, implementing, and optimizing machine learning models and data pipelines using Python and modern deep learning frameworks.
The ideal candidate has strong programming fundamentals, hands-on model development experience, and is comfortable working with large structured and unstructured datasets in production environments.
Primary Responsibilities
  • Design, develop, and maintain Python-based data processing and analytics solutions
  • Implement and optimize machine learning and deep learning models
  • Work with large datasets and streaming data sources
  • Develop reusable data structures and efficient algorithms for analysis workflows
  • Build and evaluate models for classification, prediction, and pattern recognition
  • Integrate AI/ML capabilities into software systems and pipelines
  • Collaborate with software engineers, data engineers, and analysts to deploy solutions
  • Perform model validation, performance tuning, and debugging
  • Document architecture, implementation, and usage of developed tools

Required Qualifications
  • 3+ years of professional software development experience
  • Strong Python development skills
  • Experience working with large datasets and/or streaming data
  • Proficiency in machine learning and deep learning frameworks:
  • PyTorch
  • TensorFlow
  • Keras
  • Hugging Face Transformers
  • Understanding of machine learning concepts and model architectures, including:
  • Decision Trees / Random Forests
  • LSTM / sequence models
  • Experience implementing, training, and evaluating ML models
  • Knowledge of data structures, algorithms, and performance optimization
  • Familiarity with version control (Git) and collaborative development workflows

Desired / Preferred Qualifications
  • Experience with Retrieval-Augmented Generation (RAG)
  • Experience with Model Context Protocols (MCP) or similar agent/tool interaction frameworks
  • Experience with GPU acceleration and CUDA architecture
  • Drivers, runtime, and APIs
  • Experience with deep learning and reinforcement learning libraries
  • Experience building or consuming real-time data pipelines
  • Data visualization and exploratory analysis (Matplotlib, Seaborn, Plotly, etc.)
  • Familiarity with model deployment and inference optimization
  • Experience working in containerized or distributed environments

Education
  • Bachelor's degree (or working toward a degree) in Computer Science, Data Science, Engineering, Mathematics, or related field
  • (Equivalent practical experience considered)

Nice-to-Know Technologies
  • Linux development environments
  • Jupyter notebooks
  • Docker or container basics
  • Basic command line usage

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