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Lstm Machine Learning Jobs (NOW HIRING)

Jobgether

Requirements: * 4+ years of experience in Machine Learning, Data Science, or applied AI roles. * Strong expertise in time-series forecasting techniques and models such as ARIMA, Prophet, LSTM, or ...

Staffingine LLC

Statistical Data Scientist

Edison, NJ · On-site

Design, develop, and implement statistical models and machine learning solutions to solve complex business problems. * Apply deep learning techniques including LSTM, N-BEATS, CNN, and RNN for time ...

Box

Senior Machine Learning Engineer, Shield

Redwood City, CA · On-site

$140K - $192K/yr

... applied machine learning * Lead design and implementation efforts in building, deploying and ... forecasting, LSTM, Transformers, or similar). * Experience with streaming/real-time ML systems

Box

Senior Machine Learning Engineer, Shield

Redwood City, CA · On-site

$140K - $192K/yr

... applied machine learning * Lead design and implementation efforts in building, deploying and ... forecasting, LSTM, Transformers, or similar). * Experience with streaming/real-time ML systems

Wise Skulls

AI/ML Data Scientist

Phoenix, AZ · On-site

The ideal candidate will bring deep expertise in machine learning, statistical modeling, and large ... Solid knowledge of time series modeling (ARIMA, Prophet, LSTM, state-space models, etc.

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All JobsLstm Machine Learning Jobs

Lstm Machine Learning information

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$25.5K

$42.6K

$88K

How much do lstm machine learning jobs pay per year?

As of Jun 7, 2026, the average yearly pay for lstm machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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

AspectLstm Machine LearningData Scientist
Required CredentialsKnowledge of machine learning, programming, and data analysisDegree in data science, statistics, or related field; often includes certifications
Work EnvironmentResearch and development, algorithm design, model trainingData analysis, reporting, business insights across industries
Industry UsageAI, NLP, time-series predictionBusiness, finance, healthcare, tech

While Lstm Machine Learning focuses on designing and implementing specific neural network models like LSTM for sequence data, Data Scientists analyze data broadly to generate insights, often utilizing various machine learning techniques including LSTM models. Both roles require programming skills and data analysis expertise but differ in scope and application.

Infographic showing various Lstm Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% Internship, 38% Full Time, 58% Part Time, 1% Temporary, 1% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

ML Engineer (Forecasting) | NDA

Jobgether

Remote

Full-time

Posted 6 days ago

Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a ML Engineer (Forecasting) | NDA in Netherlands.

This role offers the opportunity to work on high-impact forecasting systems that directly influence operational efficiency within a large healthcare environment. You will design and deploy machine learning models that predict demand, optimize staffing, and improve resource allocation across clinical and marketing operations. Working in a fast-paced, project-driven setting, you will contribute to building scalable, production-ready ML solutions from early discovery through to deployment. The position involves close collaboration with data, product, and cloud engineering teams to transform complex healthcare datasets into actionable insights. With a strong focus on time-series forecasting and applied machine learning, you will help shape data-driven decision-making processes that have real-world impact. This is an excellent opportunity for an ML engineer who enjoys end-to-end ownership, applied research, and building production-grade forecasting systems.

Accountabilities:
  • Design, develop, and deploy machine learning models focused on time-series forecasting and demand prediction use cases.
  • Build scalable data pipelines and ML workflows using cloud platforms such as AWS, GCP, or Azure.
  • Develop and optimize forecasting models including ARIMA/SARIMA, Prophet, LSTM, and other advanced predictive approaches.
  • Perform data preprocessing, feature engineering, and exploratory analysis on complex healthcare and operational datasets.
  • Collaborate with cross-functional teams including data engineers, product managers, and cloud specialists to deliver robust solutions.
  • Participate in the full project lifecycle, from problem definition and proof of concept through to production deployment and stakeholder presentation.
  • Ensure model reliability, scalability, and performance in production environments.
  • Continuously evaluate and improve forecasting accuracy using appropriate metrics and validation techniques.

Requirements:

  • 4+ years of experience in Machine Learning, Data Science, or applied AI roles.
  • Strong expertise in time-series forecasting techniques and models such as ARIMA, Prophet, LSTM, or equivalent approaches.
  • Advanced Python programming skills with experience using libraries such as Pandas, NumPy, scikit-learn, and PyTorch.
  • Hands-on experience deploying machine learning models into production environments.
  • Solid understanding of data preprocessing, feature engineering, and statistical modeling for time-series data.
  • Experience working with cloud platforms such as AWS, GCP, or Azure.
  • Strong knowledge of SQL and version control systems such as Git.
  • Ability to work independently in ambiguous environments with strong problem-solving and analytical thinking skills.
  • Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.
  • Advanced English proficiency required.

Benefits:

  • Competitive contract-based compensation aligned with experience and project scope.
  • Fully remote working arrangement across Europe, including the United Kingdom.
  • Opportunity to work on real-world healthcare forecasting systems with measurable operational impact.
  • Exposure to end-to-end machine learning lifecycle, from research to production deployment.
  • Collaboration with experienced engineers and data professionals in a high-impact environment.
  • Hands-on experience with modern ML stacks and cloud-native technologies.
  • Flexible engagement structure with potential for extension beyond the initial project duration.
  • Opportunity to contribute to meaningful AI applications in healthcare and operations optimization.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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