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Nights Machine Learning Trainer Jobs (NOW HIRING)

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 ...

Chefman & CHEF iQ

Machine Learning Engineer

Mahwah, NJ · On-site

... training through deployment, monitoring, and continuous improvement. • Research, evaluate, and apply emerging machine learning techniques, including computer vision, generative AI, large language ...

New

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 ...

Avride

Machine Learning Engineer

Austin, TX · On-site

They are seeking an experienced Machine Learning Engineer to design, implement, and optimize ... Develop efficient workflows for training, validation, and testing, incorporating distributed ...

Chefman

Machine Learning Engineer

Mahwah, NJ

$140K - $170K/yr

... training through deployment, monitoring, and continuous improvement. • Research, evaluate, and apply emerging machine learning techniques, including computer vision, generative AI, large language ...

New

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 ...

Qualcomm

Machine Learning Engineer

San Diego, CA · On-site

$122K - $184K/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 ...

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Title - Machine Learning ( F2F interview is required) Location - New York, NY ( Hybrid 2-3 days ... with ML model training within cloud infra such as Azure, AWS, GCP Proven track record of ...

Micron

Machine Learning Engineer

Boise, ID · On-site

Build and maintain Data/Solution Pipeline Engineering to ensure a robust and scalable data infrastructure that supports the training and deployment of machine learning models. Collaborate on data ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$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 ...

GPTZero

Machine Learning Intern

New York, NY · On-site

What we're looking for At GPTZero, we ensure that machine learning models are created for the ... Build efficient and scalable ML training and inference systems * Stay up-to-date with the latest ...

Apple

Machine Learning Engineer

Sunnyvale, CA

$147K - $272K/yr

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

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Nights Machine Learning Trainer information

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$28K

$87.3K

$112.5K

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

As of Jun 5, 2026, the average yearly pay for nights 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 Nights Machine Learning Trainer, and why are they important?

To thrive as a Nights Machine Learning Trainer, you need a strong background in machine learning principles, data analysis, and model evaluation, typically supported by a degree in computer science or a related field. Familiarity with Python, TensorFlow or PyTorch, and experience using ML training frameworks and data pipeline systems are essential. Excellent communication, adaptability to night-shift schedules, and problem-solving abilities are crucial soft skills for effective knowledge transfer and team collaboration. These skills ensure efficient model development, clear instruction during off-peak hours, and successful project outcomes in a dynamic work environment.

What are some typical challenges faced by a Nights Machine Learning Trainer and how can they be managed?

Nights Machine Learning Trainers often face challenges related to working outside standard business hours, such as limited real-time collaboration with daytime teams and adjusting to a nocturnal schedule. Managing these challenges usually involves clear communication practices, thorough handover documentation, and leveraging asynchronous tools to stay connected with colleagues. Additionally, maintaining a healthy work-life balance and prioritizing self-care are essential for sustained productivity on the night shift. Embracing these strategies can help trainers deliver effective machine learning instruction and support, even during less conventional hours.

What are Nights Machine Learning Trainers?

Nights Machine Learning Trainers are professionals who work overnight shifts to train and optimize machine learning models. Their role involves preparing datasets, setting up training processes, monitoring model performance, and making adjustments as needed. By working during nighttime hours, they ensure that machine learning systems can be developed and improved around the clock, often taking advantage of off-peak computing resources. This position is common in industries where continuous model development is critical, such as tech companies, research labs, and data-driven organizations.

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

AspectNights Machine Learning TrainerNights Data Scientist
Required CredentialsBachelor's in CS, ML certificationsBachelor's/Master's in CS, Data Science certifications
Work EnvironmentTraining sessions, workshops, online platformsData analysis, modeling, research
Employer & Industry UsageTech companies, training providersTech firms, finance, healthcare

While both roles involve working with machine learning, Nights Machine Learning Trainers focus on educating and training others in ML techniques, often in workshops or online courses. Nights Data Scientists analyze data, develop models, and derive insights. The trainer role emphasizes teaching skills, whereas the data scientist role emphasizes hands-on data analysis and model development.

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Nights Machine Learning Trainer jobs near you
Machine Learning Engineer

Machine Learning Engineer

Dark Wolf Solutions

Chantilly, VA • On-site

Other

Posted 22 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.

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