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Python Ml Developer Jobs in Illinois (NOW HIRING)

Job Title: GCP AI/ML Engineer Duration: 6 months Contract to hire Location: Chicago is the ... Orchestrate ML workflows using Python, Vertex AI, BigQuery, and Cloud Storage. * Ensure pipelines ...

Position: AI/ML Engineer Duration: 12 months Location: Chicago, IL An AI/ML Engineer designs ... Proficiency in Python, Java, or R, Golang * Machine Learning Frameworks : Expertise in tools and ...

... and DevOps โ€ข Expertise in data preprocessing and ML techniques โ€ข Experience with model ... skills (Python, R) โ€ข Cloud services and infrastructure knowledge โ€ข Agile methodologies ...

Sr. AI/ML Engineer

Deerfield, IL ยท On-site

$106K - $145K/yr

Strong Python engineering background with ML/DL frameworks: TensorFlow, PyTorch, Keras, OpenCV * Proven experience in Computer Vision tasks, including object detection, segmentation, and OCR

Python Engineer An established healthcare company is looking for a driven Python Engineer to join ... AWS SageMaker experience will be a big plus as they're in the process of bringing ML development in ...

Senior ML Engineer

Chicago, IL ยท Remote

$180K - $240K/yr

... ML team building production-grade AI voice agents used by enterprise customers like AAA and ... You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ...

They are seeking a DevOps Engineer with Python expertise to build and deploy AI models, implement ... Required : โ€ข AI/ML Expertise: Strong foundation in artificial intelligence and machine learning ...

Senior AI/ML Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

Senior AI/ML Engineer Cooley is seeking a Senior AI/ML Engineer to join the Practice Engineering ... Strong proficiency in Python for building and operating LLM-powered applications and agentic ...

Senior AI/ML Engineer

Chicago, IL ยท On-site

$107K - $147K/yr

Senior AI/ML Engineer Cooley is seeking a Senior AI/ML Engineer to join the Practice Engineering ... Strong proficiency in Python for building and operating LLM-powered applications and agentic ...

AI Developer

Mettawa, IL ยท On-site

$80/hr

Senior AI Developer Location: Mettawa, IL (Onsite) Rate: $80/hr on C2C Design, build, and deploy ... Expert-level proficiency in Python and related AI/ML frameworks (e.g., PyTorch, TensorFlow ...

Senior DevOps Engineer

Chicago, IL ยท Remote

$160K - $180K/yr

You'll pull diagnostics, identify root causes, and write custom Python/Bash scripts to overcome ... Experience with AI/ML developer tools or enterprise developer platforms * Prior experience being ...

New

Lead AI/ML Engineer - Remote

Schaumburg, IL ยท On-site +1

$100K - $132K/yr

As a Lead AI/ML Engineer within Optum Rx, you will lead the design, development, and scaling of ... using Python, Java, Scala, or similar programming languages * 3 years of experience designing ...

Lead AI/ML Engineer - Remote

Schaumburg, IL ยท On-site +1

$100K - $132K/yr

As a Lead AI/ML Engineer within Optum Rx, you will lead the design, development, and scaling of ... using Python, Java, Scala, or similar programming languages * 3+ years of experience designing ...

AI/ML Engineer

Chicago, IL ยท On-site

$77K - $135K/yr

Own AI/ML solutions end to end from design through deployment and operationalization. * Evaluate ... Strong Python expertise and software engineering practices required. * Experience building LLM ...

New

IMC is looking for a Quantitative Developer to own the full path from research to production. This ... Solid understanding of ML concepts as applied to systematic strategies, from research through ...

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Showing results 1-20

Python Ml Developer information

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and interpreting complex models, making complete replacement unlikely in the near term. MLEs need skills in programming, data analysis, and model deployment to adapt to evolving AI technologies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. Such roles usually involve leadership, strategic planning, and extensive experience in the field.

Which 3 jobs will survive AI?

For a Python ML Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as AI research scientist, data scientist, and software engineer. These jobs involve designing, interpreting, and improving AI models, which currently require advanced expertise, critical thinking, and domain knowledge that AI cannot fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

Can you do ML in Python?

Yes, Python is widely used for machine learning (ML) development due to its extensive libraries such as TensorFlow, scikit-learn, and PyTorch. Python skills are essential for a Python ML developer to build, train, and deploy ML models efficiently in various environments.
What job categories do people searching Python Ml Developer jobs in Illinois look for? The top searched job categories for Python Ml Developer jobs in Illinois are:
What cities in Illinois are hiring for Python Ml Developer jobs? Cities in Illinois with the most Python Ml Developer job openings:
Infographic showing various Python Ml Developer job openings in Illinois as of July 2026, with employment types broken down into 81% Full Time, 7% Part Time, 1% Temporary, and 11% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

GCP AI/ML Engineer

Co-Sourcing Partners

Chicago, IL โ€ข On-site

Contractor

Re-posted 26 days ago


Job description

Job Title: GCP AI/ML Engineer
Duration: 6 months Contract to hire
Location: Chicago is the preferred location, but open to candidates from anywhere in the U.S.
Role Overview
We are seeking a talented and experienced GCP AI/ML Engineer to design, build, and operationalize scalable machine learning solutions on Google Cloud Platform (GCP). This role focuses on developing production-grade ML pipelines, automating workflows, and ensuring reliability and governance across enterprise AI platforms.
The ideal candidate will have strong expertise in Vertex AI, MLOps, and cloud-native ML architectures, with a passion for turning data science models into scalable, production-ready systems.
Key Responsibilities
ML Pipeline Development & Automation
  • Build, deploy, and manage production-grade machine learning pipelines using Vertex AI Pipelines and GCP-native services.
  • Design automated workflows for data ingestion, feature engineering, model training, evaluation, and inference.
  • Orchestrate ML workflows using Python, Vertex AI, BigQuery, and Cloud Storage.
  • Ensure pipelines are modular, reusable, and scalable across use cases.

Model Operationalization (MLOps)
  • Operationalize the end-to-end ML lifecycle, including:
  • Model training
  • Deployment
  • Monitoring
  • Retraining and lifecycle management
  • Deploy models using Vertex AI endpoints with support for online and batch predictions.
  • Implement robust CI/CD pipelines for ML artifacts and workflows.
  • Enable automated model retraining and versioning strategies.

Data Integration & Feature Engineering
  • Enable seamless data flows across data lakes, warehouses, and ML platforms.
  • Design and manage feature pipelines for training and inference datasets.
  • Integrate with BigQuery, Cloud Storage, and streaming sources to support real-time and batch ML use cases.
  • Ensure consistency between training and serving data pipelines.

Model Monitoring & Performance Optimization
  • Implement model monitoring solutions to track:
  • Prediction accuracy
  • Data drift and concept drift
  • Model performance degradation
  • Set up alerting mechanisms and dashboards for proactive issue detection.
  • Optimize model performance and infrastructure for scalability, latency, and cost efficiency.

AI Platform Engineering
  • Build and enhance enterprise AI/ML platforms with a focus on:
  • Automation
  • Observability
  • Reliability
  • Develop standardized frameworks for repeatable and governed ML deployments.
  • Establish best practices for MLOps, pipeline orchestration, and infrastructure management.

Collaboration & Cross-Functional Engagement
  • Collaborate closely with:
  • Data Scientists to productionize models
  • Data Engineers for data pipeline integration
  • Architects for scalable cloud designs
  • Translate business requirements into deployable ML solutions.
  • Provide technical leadership and mentoring on ML engineering practices.

Governance, Security & Best Practices
  • Implement model governance frameworks including auditability, lineage, and compliance.
  • Ensure secure handling of data and models using IAM roles and access policies.
  • Promote best practices in:
    • Code versioning (Git)
    • CI/CD
    • Testing and validation
  • Drive documentation and standardization across ML workflows.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field.
  • 4+ years of experience in machine learning engineering or MLOps.
  • Hands-on experience with Google Cloud Platform (GCP) services:
  • Vertex AI (Pipelines, Training, Endpoints)
    oBigQuery
    oCloud Storage
  • Strong programming skills in Python.
  • Experience building and deploying end-to-end ML pipelines.
  • Strong understanding of ML lifecycle and MLOps principles.

Preferred Skills
  • Experience with TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with Kubeflow Pipelines or Apache Beam.
  • Experience with Docker and containerized deployments.
  • Knowledge of real-time ML inference and streaming architectures.
  • Hands-on experience with model monitoring tools and frameworks.
  • Understanding of feature stores and feature engineering pipelines.