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Temporary Machine Learning Scientist Jobs in Illinois

IMC Trading

Machine Learning Researcher

Chicago, IL · On-site

The role involves designing and deploying machine learning models, collaborating with trading teams ... Required : • PhD or Master's in Engineering, Math, Statistics, Computer Science, or related ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

We develop machine learning models and infrastructure to support internal team strategies and collaborate closely with our data science organization to drive efficiency and best practices. Your ...

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All JobsMachine Learning Scientist JobsTemporary Machine Learning Scientist JobsTemporary Machine Learning Scientist Jobs in Illinois

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 Illinois? For Temporary Machine Learning Scientist jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Temporary Machine Learning Scientist jobs in Illinois look for? The top searched job categories for Temporary Machine Learning Scientist jobs in Illinois are:
What cities in Illinois are hiring for Temporary Machine Learning Scientist jobs? Cities in Illinois with the most Temporary Machine Learning Scientist job openings:
Temporary Machine Learning Scientist jobs near you

Machine Learning Engineering Manager

United Airlines, Inc.

Chicago, IL • On-site

$118K - $141K/yr

Full-time

Posted 3 days ago

New

United Airlines rating

7.9

Company rating: 7.9 out of 10

Based on 341 frontline employees who took The Breakroom Quiz

7th of 26 rated airlines

Job description

Description
Job overview and responsibilities
Develops and programs integrated software algorithms to structure, analyze and leverage data in systems applications. Develops and communicates statistical modeling techniques to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. Can work with large scale computing frameworks, data analysis systems and modeling environments.
  • Design and implement key components of the Machine Learning Platform infrastructure and establish processes and best practices
  • Work cross-functionally with data scientists, data engineers, and IT teams to design, develop, deploy, and integrate high-performance, production-grade machine learning solutions and data intensive workflows
  • Partner with data scientists and data engineers to create and refine features from underlying data and build reproducible feature pipelines to train models and serve features in production
  • Partner with data platform and operations teams to solve complex data ingestion, pipeline and governance problems for machine learning solutions
  • Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads
  • Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers

Qualifications
What's needed to succeed (Minimum Qualifications):
  • Bachelor's degree in computer science, engineering, or a related technical discipline
  • 3+ years of experience in managing technical teams and projects
  • 3+ years of experience in full software lifecycle development using Python
  • 3+ years of experience leading an ML Ops team familiar with large cloud environments, Big Data technologies
  • 3+ years in software development in Python, Java, PySpark
  • 3+ Years of Experience with Machine Learning and Machine Learning workflows
  • 3+ years of experience designing and developing using technologies as Docker, Kubernetes
  • Strong software engineering experience with Python and at least one additional language such as Java, Go, Rust, or C/C++
  • Understanding of machine learning principles and techniques
  • Experience with data science tools and frameworks (e.g. PyTorch, Tensorflow, Keras, Pandas, Numpy, Spark)
  • Experience designing and developing scalable cloud native solutions using technologies such as Docker and Kubernetes and serverless services such as AWS Lambda, EKS, ECS, Fargate
  • Experience building infrastructure-as-code templates (e.g. AWS CloudFormation) and cloud-native CI/CD pipelines using tools such as AWS CodePipeline
  • Experience building ETL pipelines and working with big data technologies (e.g. Hadoop, Spark, and serverless technologies such as EMR, Redshift, S3, AWS Glue, and Kinesis)
  • Knowledge of distributed systems as it pertains to compute and data storage
  • Strong desire to experiment with and learn new technologies and stay aligned with the latest community developments in ML Ops/Engineering and cloud native
  • Excellent oral and written communication skills. Ability to prepare high-quality presentation materials and explain complex concepts and technical materials to less-technical audiences
  • Must be legally authorized to work in the United States for any employer without sponsorship
  • Successful completion of interview required to meet job qualification
  • Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):
  • AWS Certified Solution Architect (Associate or Professional)
  • Experience working as a Machine Learning Engineer or Data Scientist building and productional machine learning solutions
  • Experience building real-time event-driven stream processing solutions with technologies such as Kafka, Flink, and Spark
  • Experience with GPU acceleration (e.g. CUDA and CuDNN)
  • Experience with Kubernetes

What United Airlines employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

Social media

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