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Weekend No Experience Machine Learning Jobs in Pittsburgh, PA

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Practical experience in building, developing, and productionizing both supervised and unsupervised machine learning models * Advanced software skills in Python * Advanced ability in forming SQL ...

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

Practical experience in building, developing, and productionizing both supervised and unsupervised machine learning models * Advanced software skills in Python * Advanced ability in forming SQL ...

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

Practical experience in building, developing, and productionizing both supervised and unsupervised machine learning models * Advanced software skills in Python * Advanced ability in forming SQL ...

Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.

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Weekend No Experience Machine Learning information

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$11

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How much do weekend no experience machine learning jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for weekend no experience machine learning in Pittsburgh, PA is $17.46, according to ZipRecruiter salary data. Most workers in this role earn between $15.87 and $17.74 per hour, depending on experience, location, and employer.

What is a weekend no experience machine learning job?

A Weekend No Experience Machine Learning job is a part-time opportunity typically scheduled on weekends for individuals interested in machine learning but who have little or no prior experience in the field. These jobs are designed for beginners and may involve tasks such as data labeling, assisting with simple coding projects, or supporting research teams. They provide a great entry point for those looking to gain hands-on experience, learn industry tools, and build their resumes while balancing other commitments like school or a full-time job.

What are the key skills and qualifications needed to thrive as a weekend no experience machine learning professional?

To thrive as a Machine Learning professional, foundational knowledge in mathematics, statistics, and programming (especially Python) is essential, typically demonstrated through coursework or self-directed learning. Familiarity with machine learning libraries such as scikit-learn or TensorFlow and version control systems like Git is highly beneficial, even at an entry level. Curiosity, problem-solving abilities, and effective communication help newcomers stand out as they learn quickly and collaborate with more experienced team members. These skills and qualities are crucial to building practical expertise, contributing to projects, and adapting to the evolving demands of machine learning roles.

What kind of support and training can I expect starting a weekend no experience machine learning role?

In a weekend machine learning role designed for beginners, you can typically expect onboarding sessions, access to online learning materials, and mentorship from more experienced team members. Many organizations provide structured guidance through tutorials, code reviews, and collaborative projects to help you build foundational skills. You’ll likely be assigned manageable tasks that allow you to gradually familiarize yourself with real datasets and tools, while regular feedback ensures your steady progress. Team meetings and open communication channels are common, so don’t hesitate to ask questions and seek help as you learn.

What is the difference between Weekend No Experience Machine Learning vs Weekend Data Analyst?

AspectWeekend No Experience Machine LearningWeekend Data Analyst
Required CredentialsBasic understanding of programming, no formal certification neededBasic knowledge of data analysis tools, possibly some certifications
Work EnvironmentProject-based, flexible hours, often remotePart-time, flexible hours, often remote or on-site
Industry UsageTech, finance, healthcare, startupsBusiness, marketing, finance, consulting

Weekend No Experience Machine Learning roles focus on introductory tasks like data preprocessing and basic model training, suitable for beginners. Weekend Data Analyst positions involve analyzing datasets, creating reports, and supporting decision-making. Both roles are flexible and often part-time, but they differ in technical depth and industry focus.

What are popular job titles related to Weekend No Experience Machine Learning jobs in Pittsburgh, PA?

For Weekend No Experience Machine Learning jobs in Pittsburgh, PA, the most frequently searched job titles are:

What job categories do people searching Weekend No Experience Machine Learning jobs in Pittsburgh, PA look for?

The top searched job categories for Weekend No Experience Machine Learning jobs in Pittsburgh, PA are:

What cities near Pittsburgh, PA are hiring for Weekend No Experience Machine Learning jobs?

Cities near Pittsburgh, PA with the most Weekend No Experience Machine Learning job openings:

Full-time

Re-posted 19 days ago


Job description

About us

TeleTracking began with a simple but powerful belief that no one should wait for the care they need. More than a slogan, it's a promise to continually improve healthcare.

TeleTracking builds groundbreaking technology incorporating deep clinical expertise. Our solutions are used in the nation's largest healthcare systems and around the world to positively impact patients, families and communities.

What's your contribution to the TeleTracking story?

When you chose to bring your passion and skills to helping achieve our purpose, you'll be part of a team that understands that there's a human life behind every data point.   Your skills, curiosity, and compassion-will help fuel our innovation and achieve the TeleTracking promise of revolutionizing modern healthcare. 

About the role

We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative team at TeleTracking Technologies, focusing on improving patient care. The ideal candidate will have a strong background in developing, deploying, and optimizing machine learning models, as well as expertise in data ingestion and modeling techniques. This role requires a deep understanding of hospital operations, healthcare data, clinical workflows, and regulatory requirements (such as HIPAA or GDPR). The successful candidate will be passionate about leveraging advanced technologies to enhance patient care and operational efficiency. 

What you will do

  • Design, develop, and implement machine learning and deep learning models to address hospital-specific challenges such as patient flow optimization, resource allocation, bed management, and predictive analytics for patient outcomes.
  • Build and optimize data ingestion and modeling pipelines as needed
  • Utilize domain driven techniques and design patterns to build and contribute to technical
  • design.
  • Collaborate with cross-functional teams including data scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions.
  • Work with large-scale healthcare and hospital datasets including structured data (EHRs, hospital operational data), unstructured data (clinical notes, imaging).
  • Ensure data privacy and security, adhering to healthcare regulations such as HIPAA and GDPR, especially when working with sensitive hospital data.
  • Mentor junior engineers and data scientists, providing guidance on machine learning techniques, particularly those relevant to hospitals and healthcare systems.
  • Monitor, troubleshoot, and enhance the performance of deployed models using MLOps best practices, ensuring they operate effectively in hospital environments.
  • Write technical architectural and design documents.

What we look for

  • Proven experience in end-to-end design and deployment of machine learning models from ideation to production in healthcare or similar settings.
  • Strong programming skills and experience with object or component-oriented development software, one or more of: Python or R, with proficiency in ML frameworks, one or more of: TensorFlow, PyTorch, or Scikit-learn.
  • Expertise in NLP, computer vision, or other specialized machine learning techniques applicable to healthcare and hospital environments.
  • Deep knowledge of a scripting or statistical programming language (Python preferred). Ability to efficiently work with very large datasets and deal with non-standard machine learning datasets (class-imbalances, sparse matrices, etc.)
  • Assess model performance; train multiple models; carry out tuning.  Run A/B tests on models.
  • Comfortable writing complex SQL queries and developing python packages.
  • Experience with cloud-based management and hosting, one or more of: AWS, Azure, GCS, CloudFormation, Terraform, or Ansible.Interest in developing services as well as the underlying infrastructure
  • Experience with database management system software, one or more of: Oracle, MSSQL, MongoDB, MySQL, DynamoDB, or PostgreSQL.
  • Experience with Version Control Software, one or more of: git, Mercurial, CVS, TFS, or Subversion.
  • Strong understanding and experience executing several software development methodologies and life cycles. Ability to understand and translate business requirements into technical specifications.
  • Experience with agile development practices.
  • Excellent written and oral communication skills. Adept and presenting complex topics, influencing, and executing with timely / actionable follow-through.
  • Strong analytical and problem-solving skills with the ability to convert information into practical training deliverables. Uses rigorous logic and methods to solve difficult problems.
  • Knowledge of clinical workflows and hospital operations, and how technology can enhance efficiency and patient care.
  • Familiarity with healthcare-specific machine learning challenges, such as data imbalance, longitudinal data, and real-time processing in hospital environments.
  • Be an active listener, probe requirements for all projects from relevant stakeholders, stay nimble and willing to produce rapid iterations.

Education

  • Bachelor's degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 7 or more years of experience.
  • Master's or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 5 or more years of experience. (preferred)

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.