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Temporary Machine Learning Scientist Jobs in Pennsylvania

Machine Learning Engineer III

Pittsburgh, PA · On-site

$111K - $133K/yr

... scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions. • Work with large-scale ...

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an ... Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a ...

MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree) Nice to Have * Experience with drone, robotics, or autonomous ...

... Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree) Preferred : • Experience with drone, robotics, or autonomous systems perception ...

MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree) Nice to Have * Experience with drone, robotics, or autonomous ...

MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree) Nice to Have * Experience with drone, robotics, or autonomous ...

Showing results 21-40

Temporary Machine Learning Scientist information

What is the difference between Temporary Machine Learning Scientist vs Data Scientist?

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a temporary machine learning scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.
What are popular job titles related to Temporary Machine Learning Scientist jobs in Pennsylvania? For Temporary Machine Learning Scientist jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Scientist jobs in Pennsylvania look for? The top searched job categories for Temporary Machine Learning Scientist jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Temporary Machine Learning Scientist jobs? Cities in Pennsylvania with the most Temporary Machine Learning Scientist job openings:
Infographic showing various Temporary Machine Learning Scientist job openings in Pennsylvania as of July 2026, with employment types broken down into 17% Internship, and 83% Full Time. Highlights an 59% In-person, and 41% Remote job distribution.

Machine Learning Engineer III

TeleTracking Technologies, Inc.

Pittsburgh, PA • On-site

Full-time

Re-posted 10 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.