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Temporary Machine Learning Trainer Jobs (NOW HIRING)

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

Strong experience designing, building, training, and testing machine learning models end-to-end. * Proven ability to work with raw, unstructured, or incomplete data, including data collection ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA

We have an opening for a Machine Learning (ML) Bioengineer to conduct research training and evaluating next-generation clinical, protein and genome language models. You will join the Bioresilience ...

Ksb

Machine Learning Engineer

Grovetown, GA

Machine Learning Engineer KSB GIW, Inc. Department: Engineering, Research & Development Reports to ... Foundational understanding of neural networks, model training, and optimization * Experience with ...

Constellation Space

Machine Learning Engineer

Seattle, WA · On-site

$120K - $180K/yr

Build robust MLOps pipelines for continuous training and integration of models using telemetry data ... Proven experience deploying machine learning models into production. * Strong software engineering ...

ManTech International

Machine Learning Engineer

$128K - $214K/yr

Collaborate with cross-functional teams-including data scientists, engineers, and architects-to build machine learning models, training tools, and simulation environments that support business ...

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

Contribute to the design of data pipelines and infrastructure for training, testing, and validating ... Stay current with the latest Machine Learning research for wireless and embedded systems. * Perform ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're building a new type of firm, where live capital is the training ground for an intelligence that compounds with every signal. About the Role At Poesis, machine learning and artificial ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build ... training, evaluation, deployment, and monitoring. You will work both independently and ...

Serve Robotics

$225K - $260K/yr

By optimizing distributed training pipelines, neural network architectures, and data processing ... Hands-on experience training machine learning models across multiple GPUs or compute nodes ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

... training, inference, labeling, and evaluation • Judiciously combine open-source solutions and ... Machine Learning, including ownership of projects throughout the entire ML Lifecycle • ...

MatrixSpace

Machine Learning Engineer

Burlington, MA · Remote

$165K - $200K/yr

Build and improve machine learning infrastructure, tooling, and training pipelines that enable faster experimentation and more efficient model development. * Design and implement AI agents, agentic ...

New

Anytime AI

Machine Learning Engineer

OR · Remote

$100K - $200K/yr

Position Overview As a Machine Learning Engineer, you will be instrumental in crafting and refining ... Experience in training Large Language Models. * Web development experience or willingness to ...

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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 Jul 10, 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 July 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $87,325 per year, or $42 per hour.
Machine Learning Engineer

Machine Learning Engineer

Machina Labs

Chatsworth, CA • On-site

$160K - $190K/yr

Full-time

Re-posted 27 days ago

Job description

About Machina Labs
Engineering moves at software speed. Manufacturing doesn't. Yet.
Machina Labs is changing that. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By integrating advanced metal forming, robotics, and automated production inside a flexible factory architecture, we enable customers to move from prototype to production in weeks, not years.
Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that defense, aerospace, and advanced mobility programs will run on.
If you want to work on hard problems that matter and see them fly, drive, and defend, this is the place.
Job Description:
We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy machine learning models that power our robotic sheet metal forming systems. You'll work closely with our engineering team to transform raw data into actionable intelligence, enabling our robots to produce parts with greater precision, speed, and adaptability.
This is a hands-on role for someone who thrives at the intersection of research and production, someone who is just as comfortable wrangling messy datasets as they are architecting scalable ML pipelines. If you're passionate about applying machine learning to real-world manufacturing challenges, we'd love to hear from you.
Key Responsibilities:
  • Design, build, train, evaluate, and deploy machine learning models to support and improve our robotic manufacturing processes.
  • Identify, collect, clean, and organize data from diverse sources to construct high-quality datasets for model training and evaluation.
  • Develop and maintain scalable ML pipelines and infrastructure using cloud platforms, with a focus on Azure.
  • Leverage Databricks and Apache Spark for large-scale data processing and model development.
  • Collaborate with cross-functional teams, including robotics, software, and manufacturing engineers to integrate ML solutions into production workflows.
  • Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges.
  • Write clean, well-documented, and production-quality Python code.
  • Communicate findings, results, and recommendations to both technical and non-technical stakeholders.
  • Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges.
  • Write clean, well-documented, and production-quality Python code.
  • Communicate findings, results, and recommendations to both technical and non-technical stakeholders.

Required Background & Experience:
  • Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands-on experience in machine learning and AI; or a Ph.D. in a relevant field with 3+ years of experience.
  • Strong experience designing, building, training, and testing machine learning models end-to-end.
  • Proven ability to work with raw, unstructured, or incomplete data, including data collection, cleaning, labeling, and dataset construction.
  • Proficiency in Python for ML development, data processing, and scripting.
  • Familiarity with cloud computing frameworks and services, with a preference for Microsoft Azure.
  • Experience with Databricks and Apache Spark for data engineering and model development.

Preferred Qualifications:
  • Machine learning experience in CAD and computational geometry applications.
  • Experience working in the industrial or manufacturing space.
  • Experience with robotics, including robotic perception, control, or planning.

*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this role. Duties and responsibilities may change based on business needs.
$160,000 - $190,000 a year
The base salary range for this role is dependent on experience, qualifications, and overall alignment with the scope of the position.
In addition to base compensation, Machina Labs offers a competitive benefits package and stock option participation.
Machina Labs is an Affirmative Action and Equal Employment Opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law.
We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.
*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this role. Duties and responsibilities may change based on business needs.
Machina Labs is an Affirmative Action and Equal Employment Opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law.
We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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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