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Temporary Machine Learning Trainer Jobs (NOW HIRING)

Machine Learning Engineer

Manhattan, NY · On-site

$170.17 - $255.26/hr

Develop machine learning & deep learning models using Python, including data preprocessing, feature engineering, model training, and evaluation for large-scale datasets * Use SQL for large-scale data ...

The role involves developing and optimizing machine learning models, managing large-scale datasets ... Develop efficient workflows for training, validation, and testing, incorporating distributed ...

Operationalize ML model training at serving at enterprise scale * Stay abreast of the latest advancements in machine learning What you should have: * Master's Degree/Bachelor's Degree in Machine ...

DUTIES & RESPONSIBILITIES * Assist in developing and training machine learning models * Support the creation and maintenance of data pipelines * Help deploy ML models into production under guidance

Responsibilities : • Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling. • Scale and maintain machine learning model training ...

Machine Learning Compiler

New York, NY · On-site

$140K - $211K/yr

Principal Duties and Responsibilities: • Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model efficiency software tools with new features and ...

Operationalize ML model training at serving at enterprise scale * Stay abreast of the latest advancements in machine learning What you should have: * Master's Degree/Bachelor's Degree in Machine ...

Applies Machine Learning knowledge to assist in extending training or runtime frameworks or model efficiency software tools with new features and optimizations.Assists in the modeling, architecture ...

Job Summary We are seeking an experienced Machine Learning Engineer with strong hands-on expertise in building, training, deploying, monitoring, and maintaining production machine learning models.

DUTIES & RESPONSIBILITIES * Assist in developing and training machine learning models * Support the creation and maintenance of data pipelines * Help deploy ML models into production under guidance

$160 - $190/hr

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 ...

Own the full machine learning lifecycle, from data preparation and model training through deployment, monitoring, and continuous improvement. Research, evaluate, and apply emerging machine learning ...

Showing results 21-40

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 Aug 22, 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 is a temporary machine learning trainer?

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.

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 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 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 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:

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, 72% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $87,325 per year, or $42 per hour.

Machine Learning Engineer

Full Scope

Fort George G Meade, MD • On-site

$120 - $180/hr

Other

This job post has expired today. Applications are no longer accepted.


Job description

Job Title:Machine Learning Engineer

Location:Fort Meade, MD

Required Clearance: TS/SCI w/ Full-Scope Poly

Salary:Competitive

We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in machine learning, data science, and software engineering. You will work closely with data scientists, engineers, and product managers to design, develop, and deploy machine learning models and solutions that drive business value.

Key Responsibilities
  • Design, develop, and implement machine learning models and algorithms to solve real-world problems.
  • Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
  • 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 into production and monitor their performance.
  • Develop and maintain machine learning pipelines and infrastructure.
  • Stay current with the latest research and advancements in machine learning and AI.
  • Participate in code reviews, team meetings, and contribute to a collaborative development environment.
  • Document processes, models, and findings comprehensively.
Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. Ph.D. is a plus.
  • Proven experience as a Machine Learning Engineer or in a similar role.
  • Strong proficiency in programming languages such as Python, R, or Java.
  • Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
  • Solid understanding of machine learning algorithms, including supervised and unsupervised learning, reinforcement learning, and deep learning.
  • Experience with data processing tools like Pandas, NumPy, and data visualization tools such as Matplotlib or Seaborn.
  • Familiarity with cloud platforms like AWS, Google Cloud, or Azure for model deployment and scaling.
  • Strong problem-solving skills and the ability to think critically and analytically.
  • Excellent communication and teamwork skills.
Preferred Qualifications
  • Experience with natural language processing (NLP) and computer vision.
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of software development best practices and version control systems like Git.
  • Experience with containerization tools like Docker and orchestration tools like Kubernetes.
  • Previous experience in a fast-paced, startup environment.
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