ZipRecruiter

Log In

1

Temporary Machine Learning Trainer Jobs (NOW HIRING)

Apple

Machine Learning Engineer, Proactive

Cupertino, CA

$212K - $318K/yr

... training, optimization, and deployment Consistent track record of researching, inventing and/or shipping advanced machine learning models Outstanding communication and interpersonal skills with ...

Full Scope

Machine Learning Engineer

Reston, VA

Conduct data analysis and preprocessing to ensure high-quality data for model training. * Optimize and fine-tune models for performance, accuracy, and scalability. * Deploy machine learning models ...

Aivra Health LLC

$28 - $45/hr

Key Responsibilities * Assist in building and training machine learning and deep learning models * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects ...

Avride

Machine Learning Engineer

Austin, TX

Develop efficient workflows for training, validation, and testing, incorporating distributed ... Strong understanding of fundamental machine learning algorithms and neural network techniques.

Aivra Health LLC

$28 - $45/hr

Key Responsibilities * Assist in building and training machine learning and deep learning models * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

Aivra Health LLC

$28 - $45/hr

Key Responsibilities * Assist in building and training machine learning and deep learning models * Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) * Implement ...

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine ... Build and optimize end-to-end ML pipelines for data ingestion, feature engineering, model training ...

Hive

Machine Learning Manager

Seattle, WA

$180K - $250K/yr

We're interested in experimenting with new models, new ideas, and training on novel datasets. Our ideal candidate has experience managing a team of machine learning engineers working on ML projects ...

RIT Solutions

Machine Learning Engineer

Fremont, CA

Build and maintain end-to-end machine learning pipelines, including data ingestion, preprocessing, model training, deployment, and monitoring. * Evaluate and benchmark machine learning models using ...

Samprasoft

Machine Learning Engineer

Mclean, VA

Design and implement Machine Learning algorithms and models into software solutions for our enterprise customers by using common machine learning frameworks, including establishing and training ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Solid understanding of machine learning, deep learning fundamentals and optimizations; practical expertise in designing, training and improving deep neural networks. Experience with cutting edge ...

next page

Showing results 1-20

All JobsTemporary Machine Learning Trainer Jobs

Temporary Machine Learning Trainer information

See salary details

$28K

$87.3K

$112.5K

How much do temporary machine learning trainer jobs pay per year?

As of Jun 19, 2026, the average yearly pay for temporary machine learning trainer in the United States is $87,325.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,000.00 and $111,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Trainer, and why are they important?

To thrive as a Temporary Machine Learning Trainer, you need a solid background in machine learning concepts, data analysis, and model evaluation, usually supported by a relevant degree or experience in computer science or a related field. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or scikit-learn), and educational tools is typically required. Strong communication, adaptability, and instructional skills help trainers effectively convey complex topics and respond to diverse learner needs. These skills ensure trainees gain practical knowledge and confidence, contributing to successful training outcomes and organizational goals.

What are some common challenges faced by Temporary Machine Learning Trainers, and how can they be managed effectively?

Temporary Machine Learning Trainers often face the challenge of quickly adapting to new team environments and rapidly understanding existing workflows. Additionally, they may need to balance delivering training sessions with handling updates to curriculum or technology. Effective communication with permanent staff and staying up-to-date with the latest machine learning tools can help manage these challenges. Being proactive in seeking feedback and clarifying expectations early on can also contribute to a smoother transition and more impactful training sessions.

What is the difference between Temporary Machine Learning Trainer vs Data Scientist?

AspectTemporary Machine Learning TrainerData Scientist
CredentialsRelevant certifications (e.g., AWS, Google Cloud), technical trainingAdvanced degrees (Master's or PhD) in data science, statistics, or related fields
Work EnvironmentTraining sessions, workshops, corporate training settingsData analysis, modeling, research environments, often in offices or labs
Employer & Industry UsageTech companies, educational institutions, consulting firmsTech, finance, healthcare, research organizations

While both roles involve working with data and machine learning, a Temporary Machine Learning Trainer primarily focuses on educating and training teams or clients on machine learning tools and concepts. In contrast, a Data Scientist develops models, analyzes data, and derives insights for decision-making. The roles differ mainly in their focus—training versus data analysis—though they share foundational technical skills.

What are Temporary Machine Learning Trainers?

Temporary Machine Learning Trainers are professionals hired on a short-term or contract basis to develop, implement, and refine machine learning models or to train teams in machine learning techniques. Their responsibilities often include preparing training data, selecting appropriate algorithms, and ensuring models are accurate and efficient. They may also provide guidance to organizations on best practices and help upskill employees in machine learning concepts. These roles are typically project-based and may last from a few weeks to several months, depending on organizational needs.
More about Temporary Machine Learning Trainer jobs
What cities are hiring for Temporary Machine Learning Trainer jobs? Cities with the most Temporary Machine Learning Trainer job openings:
What are the most commonly searched types of Machine Learning Trainer jobs? The most popular types of Machine Learning Trainer jobs are:
What states have the most Temporary Machine Learning Trainer jobs? States with the most job openings for Temporary Machine Learning Trainer jobs include:
What job categories do people searching Temporary Machine Learning Trainer jobs look for? The top searched job categories for Temporary Machine Learning Trainer jobs are:
Temporary Machine Learning Trainer jobs near you
Infographic showing various Temporary Machine Learning Trainer job openings in the United States as of June 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $87,325 per year, or $42 per hour.
Machine Learning Engineer

Machine Learning Engineer

Dark Wolf Solutions

Herndon, VA • On-site

Full-time

Posted 4 days ago

Job description

Dark Wolf constructs and deploys data management and analytics solutions for the defense and intelligence communities. We're proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission's biggest challenges.
Dark Wolf is seeking a highly motivated and self-directed professional to fill the role of Machine Learning (ML) Engineer to support our team in Northern Virginia.
Responsibilities:
  • Design, develop, and implement machine learning models and algorithms to solve specific business problems.
  • Build and maintain scalable and robust machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
  • Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure.
  • Collaborate closely with data scientists, software engineers, and product managers to understand requirements and translate them into practical ML solutions.
  • Experiment with different machine learning techniques and algorithms to identify the most effective approaches for given problems.
  • Evaluate model performance using appropriate metrics and iterate on models to improve accuracy, efficiency, and scalability.
  • Monitor and maintain deployed models, ensuring their reliability and performance in production environments.
  • Troubleshoot and resolve issues related to machine learning models and pipelines.
  • Stay up-to-date with the latest advancements in machine learning, deep learning, and related fields.
  • Contribute to the development of best practices and standards for machine learning development and deployment within the team.
  • Document machine learning models, experiments, and deployment processes.
  • Potentially work with large datasets and big data technologies.
  • Optimize machine learning models for performance and efficiency.

Qualifications:
  • Master's in computer science, Machine Learning, or higher level degree is preferred with of 3+ years of related industry experience in Machine Learning, Computer Science, Data Science or related fields.
  • Demonstrated hands-on experience in developing and deploying machine learning models in a production environment.
  • Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc.
  • Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures).
  • Experience with data preprocessing, feature engineering, and data visualization techniques.
  • Familiarity with data storage and processing technologies (e.g., SQL, NoSQL databases, Spark, Hadoop).
  • Experience with cloud platforms (e.g., AWS, Azure, GCP) and their machine learning services.
  • Understanding of software development principles, version control (e.g., Git), and CI/CD pipelines.
  • Strong analytical and problem-solving skills with the ability to interpret data and draw meaningful conclusions.
  • Excellent communication and collaboration skills to effectively communicate technical concepts to both technical and non-technical audiences.

Preferred Skills:
  • Experience with specific areas of machine learning such as Natural Language Processing (NLP), Computer Vision, or Recommender Systems.
  • Experience with MLOps practices and tools for automating and monitoring machine learning workflows.
  • Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
  • Experience with building and deploying RESTful APIs.
  • Familiarity with big data technologies and distributed computing.
  • Experience with statistical modeling and inference.

Position Clearance Requirement:
TS/SCI with Full-Scope Polygraph
This position is located in Chantilly/Herndon, VA.
We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

Apply