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Machine Learning Trainer Jobs (NOW HIRING)

Build and maintain systems and pipelines supporting machine learning training, evaluation, inference, and monitoring * Deploy and support machine learning models in production environments * Write ...

POSITION SUMMARY As a Fintech company where Machine Learning (ML) is one of the key drivers of ... Familiarity with training or fine-tuning large-scale models, Sequence Transformer models * Interest ...

We are looking for an exceptional candidate with a proven track record of training and deploying ... Develop machine learning models that revolutionize our customers' businesses. Treeswift develops ...

Machine Learning Engineer (AI Data Trainer) About the Role What if your expertise in machine learning could directly influence how the next generation of AI models reason, plan, and solve complex ...

Machine Learning Engineer - AI Data Trainer * Location: Remote About the job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting-edge AI models.

Description SAIC is seeking a talented and experienced Machine Learning Developer to join our ... training. We are a team of 23,000 strong driven by mission, united purpose, and inspired by ...

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

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

... training, evaluation, and deployment. • Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure. • Collaborate closely with data ...

Key Responsibilities: - Design and implement machine learning models and algorithms to solve business problems - Collaborate with data scientists to gather and preprocess data for model training and ...

... training, evaluation, and deployment. • Transform machine learning models into deployable APIs and integrate them with existing applications and infrastructure. • Collaborate closely with data ...

Implementation and Training of Appropriate Models from Literature. * Characterization of Error in Models. * Iterative Optimization of Models. * On the engineering side of development, the Machine ...

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 ...

... engineering, training data collection and generation, model fine-tuning and model evaluation ... Machine Learning, or a related field.\nAt least 2 years of experience in various state-of-the-art ...

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Machine Learning Trainer information

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$28K

$87.3K

$112.5K

How much do machine learning trainer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for 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 Machine Learning Trainer job?

A Machine Learning Trainer is responsible for preparing and curating datasets, fine-tuning machine learning models, and optimizing algorithms for accuracy and efficiency. They work closely with data scientists and engineers to improve model performance and ensure high-quality training data. This role involves tasks like labeling data, selecting features, and implementing preprocessing techniques. Additionally, they may develop training methodologies and evaluate models using various metrics to enhance their effectiveness.

What are the key skills and qualifications needed to thrive in the Machine Learning Trainer position, and why are they important?

To thrive as a Machine Learning Trainer, you need a solid background in computer science, statistics, and machine learning concepts, often supported by relevant academic degrees and industry experience. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and certifications like TensorFlow Developer or AWS Machine Learning are valuable assets. Excellent communication, patience, and adaptability allow trainers to effectively convey complex concepts to diverse learners. These skills ensure effective teaching, learner engagement, and successful knowledge transfer in a rapidly evolving technological landscape.

What are the typical challenges faced by a Machine Learning Trainer in the workplace?

Machine Learning Trainers often encounter the challenge of explaining complex algorithms and abstract mathematical concepts to learners with varying levels of expertise. Adapting course materials to suit different learning styles and staying current with the latest advancements in machine learning require continuous self-development. Trainers may also need to collaborate closely with data scientists, engineers, and curriculum developers to ensure their training aligns with real-world applications. Overcoming these challenges not only enhances teaching effectiveness but also contributes to the overall growth of both trainers and their learners.
What cities are hiring for Machine Learning Trainer jobs? Cities with the most 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 Machine Learning Trainer jobs? States with the most job openings for Machine Learning Trainer jobs include:
Infographic showing various Machine Learning Trainer job openings in the United States as of May 2026, with employment types broken down into 2% As Needed, 37% Full Time, 59% Part Time, and 2% Contract. Highlights an 98% Physical, and 2% Remote job distribution, with an average salary of $87,325 per year, or $42 per hour.

Machine Learning Engineer

ExtendMyTeam

Cary, NC

Full-time

Posted 15 days ago


Job description

Join a high-growth financial technology organization focused on building modern digital banking, payments, lending, and risk solutions for financial institutions and fintech partners. This team is investing in machine learning and analytics capabilities to help improve fraud detection, predictive insights, and operational decision-making across customer-facing products.

This is an opportunity to work on applied machine learning systems that directly support real-world fraud and risk workflows. The team owns solutions end-to-end and is focused on building scalable, production-ready ML applications that deliver measurable customer impact.

Position Summary

We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual will work closely with software engineers, data scientists, and product teams to operationalize machine learning models, improve ML infrastructure, and support scalable analytics workflows.

This is a hands-on engineering role focused on production systems, model deployment, APIs, pipelines, and ML operations rather than purely research-oriented machine learning work.

Responsibilities

  • Build and maintain systems and pipelines supporting machine learning training, evaluation, inference, and monitoring

  • Deploy and support machine learning models in production environments

  • Write clean, scalable, maintainable, and well-tested Python code

  • Support monitoring, troubleshooting, and optimization of production ML systems and data pipelines

  • Collaborate cross-functionally with engineering, data science, and product teams to operationalize ML solutions

  • Improve the reliability, scalability, and performance of ML infrastructure and services

  • Contribute to tooling and processes that support the machine learning development lifecycle

  • Participate in code reviews, technical discussions, and collaborative problem solving

Required Qualifications

  • 2+ years of experience in machine learning engineering, software engineering, or related technical experience

  • Strong Python development experience

  • Experience working with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

  • Experience deploying or supporting machine learning models in production environments

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Exposure to cloud platforms such as AWS, GCP, or Azure

  • Understanding of taking machine learning models from research/development into production systems

Additional Information

  • Hybrid work environment based in Cary, NC

  • Applicants must be authorized to work in the U.S. without sponsorship

  • Competitive compensation, benefits, flexible time off, and career development opportunities