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Machine Learning Engineer

Techgroup America Inc.

Hybrid in Chicago, Illinois • Today

Easy Apply

Contract

Depends on Experience

Senior Lead Machine Learning Engineer

Capital One

Chicago, Illinois • Today

Full-time

USD 209,000.00 - 238,500.00 per year

Senior Machine Learning Engineer

Apex Systems

Chicago, Illinois • Today

Easy Apply

Full-time

$90 - $100 per hour

Machine Learning Engineer

Crowe LLP

Chicago, Illinois • 11d ago

Full-time

USD 62,000.00 - 100,000.00 per year

Machine Learning Engineer

Crowe LLP

Chicago, Illinois • Today

Full-time

USD 62,000.00 - 100,000.00 per year

Business Consultant - AI/ML Engineer

NTT DATA, Inc.

Chicago, Illinois • Today

Full-time

USD 91,000.00 - 115,000.00 per year

Machine Learning Engineer, Associate Director (Chicago)

Fitch Group

Chicago, Illinois • Today

Full-time

CAD 140,000.00 - 175,000.00 per year

Machine Learning Engineer, Associate Director (Chicago)

Fitch Group

Chicago, Illinois • Today

Full-time

USD 140,000.00 per year

Hardware Machine Learning Engineer

IMC

Chicago, Illinois • Today

Full-time

USD 200,000.00 - 225,000.00 per year

Senior AI/ML Engineer

Navistar International Corp.

Lisle, Illinois • Today

Full-time

USD 112,000.00 - 168,000.00 per year

ML Engineer (Machine Learning)

Dexian DISYS

Remote or Hybrid • Today

Easy Apply

Contract

$45 - $50 per hour

Sr. AI/ML Engineer - Remote

UnitedHealth Group

Remote or Schaumburg, Illinois • Today

Full-time

USD 120,100.00 - 214,500.00 per year

AI/ML Engineer - Chicago, IL, Minneapolis, MN, Detroit, MI, Madison, WI, Columbus, OH.

TechniPros, LLC

Remote or Chicago, Illinois • Today

Easy Apply

Contract

Depends on Experience

Machine Learning Engineer / Forward Deployed

Oscar Technology

Remote • Today

Easy Apply

Full-time

$250000 - $300000 per annum

Staff Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home - G

Next Step Systems

Remote • Today

Easy Apply

Full-time

$150,000 - $170,000

Senior Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home - G

Next Step Systems

Remote • Today

Easy Apply

Full-time

$170,000 - $190,000

Principal Machine Learning Engineer, Artificial Intelligence (AI) Required, Work From Home - G

Next Step Systems

Remote • Today

Easy Apply

Full-time

$170,000 - $200,000

Lead AI ML Engineer - AWS Connect - Remote

UnitedHealth Group

Remote or Schaumburg, Illinois • Today

Full-time

USD 112,700.00 - 193,200.00 per year

Machine Learning Software Engineer 1

Crowe LLP

Chicago, Illinois • Today

Full-time

USD 62,000.00 - 100,000.00 per year

Machine Learning Software Engineer 1

Crowe LLP

Chicago, Illinois • 11d ago

Full-time

USD 62,000.00 - 100,000.00 per year

Machine Learning Engineer

Dice Talent & Staffing Solutions

Remote • 21d ago

Easy Apply

Full-time

150000 - 300000

Machine Learning Engineer

Sift Science, Inc

Remote or San Francisco, California • Today

Full-time

USD 140,000.00 - 190,000.00 per year

Machine Learning Engineer

Lyntris Inc

Remote • Today

Full-time

Machine Learning Engineer

Takeda pharmaceutical

Remote • Today

Full-time

USD 160,000.00 per year

Machine Learning Engineer I

V-Soft Consulting Group, Inc

Remote • 4d ago

Easy Apply

Contract

Depends on Experience

Principal Machine Learning Engineer

iHerb inc

Remote • 27d ago

Full-time

USD 205,000.00 - 230,000.00 per year

Principal Machine Learning Engineer

Atlassian Inc.

Remote or Mountain View, California • Today

Full-time

USD 236,700.00 - 309,025.00 per year

AI/ML Engineer

SRI Tech Solutions

Remote • Yesterday

Easy Apply

Part-time, Third Party

45 - 55

Machine Learning Engineer

Atlassian Inc.

Remote or Seattle, Washington • Today

Full-time

USD 178,200.00 - 232,650.00 per year

AI/ML Engineer

QUANTUM TECHNOLOGIES LLC

Remote • 9d ago

Easy Apply

Contract

$70 - $90

Job Details

Skills

ML engineer
Machine Learning engineer
AI/ML engineer
Python
MLOPS
ML Ops
deploy ML models

Summary

Role:- Machine Learning Engineer
Location:- Hybrid at Chicago, IL

There is an ML model they built to predict their account balances.
It is potentially ready to be used for income simulation forecasting that has been manual and now they can automate and use this model as a potential input.
If the model is accurate enough and they can explain it well enough they can push this.
This is a lot more about technical expertise and technical leadership than strategic. More Engineer.
AWS Sagemaker. Switching from AWS to Databricks. Expertise in more than one tool is helpful. AWS and Databricks. LLM. Cloud formation Lambda. Python. Pyspark AWS Glue. ML Ops Sagemaker.
We had a very strong profile submitted that the team really liked, but they identified a candidate another candidate with more hands on keyboard experience in ML Ops in Sagemaker.
More senior, experienced ML Engineer that has built similar models and is familiar with other tech ologies, including AWS SageMaker and Databricks (currently using AWS Forecast), Jupyter Notebook, AWS Bedrock, XGBoost.
AWS Suite
Python
Amazon ECR
Version Control
Integration with ADO
Building, enhancing, explaining, risk and audit experience to understand controls.
Looking at model optimization and metrics and importance. How to incrementally improve those. Getting the optimized version. Good stakeholder engagement experience.
Data ingestion: RDS database, SQL Server, FRED Data (Federal Reserve Economic Data), MSRP . org (Municipal Securities Rulemaking Board).
Onsite Tuesday and Thursday ideally, but they can be flexible if someone wants other days.

Job Description - Duties:

Collaborate with data scientists, software engineers, and DevOps teams to develop and deploy ML models
Build, test, and deploy ML Ops pipelines on AWS
Manage and monitor production ML systems to ensure optimal performance, reliability, and scalability
Design and implement automated workflows for data cleaning, feature engineering, model training, and model deployment
Develop and maintain documentation for ML Ops processes and procedures
Continuously improve ML Ops pipeline performance and efficiency
Troubleshoot and resolve issues related to ML model performance, data quality, and infrastructure

Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Minimum of 5-7 years of experience in ML Ops, DevOps, or related roles
Strong knowledge of AWS services and tools related to ML Ops, such as SageMaker, Step Functions, Lambda, and CloudFormation
Hands-on experience building and deploying ML models in production using AWS
Proficiency in Python and/or other programming languages commonly used in ML, such as R, Java, or Scala
Familiarity with containerization technologies such as Docker and Kubernetes
Excellent problem-solving skills and attention to detail
Ability to work independently as well as in a team environment
Strong communication skills and ability to explain technical concepts to non-technical stakeholders

Knowledge, Skills, Abilities and Behaviors:

Knowledge of machine learning concepts, algorithms, and frameworks.
Knowledge of software engineering principles and best practices, such as version control, continuous integration, and agile development methodologies.
Strong understanding of data analysis and data manipulation techniques.
Ability to design and implement scalable, secure, and fault-tolerant ML Ops pipelines on AWS.
Ability to analyze and interpret data to identify patterns, trends, and anomalies, using advanced data manipulation techniques.
Outstanding communication skills (verbal, written, visualization, and listening).
Self-starter who can work independently as well as in a team setting.
Hands-on technologist with the ability to help drive the strategy and mentor others.
Giving and receiving effective feedback across all interactions.
Interest in understanding customer perspectives to aid in the development of the right solution.
Interest in understanding business needs to aid in developing solutions that are right for the broader organization.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91132487
Position Id: 9076743
Posted 15 hours ago

Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Contact the job poster

Gaurav Verma

Recruiter @ Techgroup America Inc.

View Profile

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Job Details

Skills

ML engineer
Machine Learning engineer
AI/ML engineer
Python
MLOPS
ML Ops
deploy ML models

Summary

Role:- Machine Learning Engineer
Location:- Hybrid at Chicago, IL

There is an ML model they built to predict their account balances.
It is potentially ready to be used for income simulation forecasting that has been manual and now they can automate and use this model as a potential input.
If the model is accurate enough and they can explain it well enough they can push this.
This is a lot more about technical expertise and technical leadership than strategic. More Engineer.
AWS Sagemaker. Switching from AWS to Databricks. Expertise in more than one tool is helpful. AWS and Databricks. LLM. Cloud formation Lambda. Python. Pyspark AWS Glue. ML Ops Sagemaker.
We had a very strong profile submitted that the team really liked, but they identified a candidate another candidate with more hands on keyboard experience in ML Ops in Sagemaker.
More senior, experienced ML Engineer that has built similar models and is familiar with other tech ologies, including AWS SageMaker and Databricks (currently using AWS Forecast), Jupyter Notebook, AWS Bedrock, XGBoost.
AWS Suite
Python
Amazon ECR
Version Control
Integration with ADO
Building, enhancing, explaining, risk and audit experience to understand controls.
Looking at model optimization and metrics and importance. How to incrementally improve those. Getting the optimized version. Good stakeholder engagement experience.
Data ingestion: RDS database, SQL Server, FRED Data (Federal Reserve Economic Data), MSRP . org (Municipal Securities Rulemaking Board).
Onsite Tuesday and Thursday ideally, but they can be flexible if someone wants other days.

Job Description - Duties:

Collaborate with data scientists, software engineers, and DevOps teams to develop and deploy ML models
Build, test, and deploy ML Ops pipelines on AWS
Manage and monitor production ML systems to ensure optimal performance, reliability, and scalability
Design and implement automated workflows for data cleaning, feature engineering, model training, and model deployment
Develop and maintain documentation for ML Ops processes and procedures
Continuously improve ML Ops pipeline performance and efficiency
Troubleshoot and resolve issues related to ML model performance, data quality, and infrastructure

Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Minimum of 5-7 years of experience in ML Ops, DevOps, or related roles
Strong knowledge of AWS services and tools related to ML Ops, such as SageMaker, Step Functions, Lambda, and CloudFormation
Hands-on experience building and deploying ML models in production using AWS
Proficiency in Python and/or other programming languages commonly used in ML, such as R, Java, or Scala
Familiarity with containerization technologies such as Docker and Kubernetes
Excellent problem-solving skills and attention to detail
Ability to work independently as well as in a team environment
Strong communication skills and ability to explain technical concepts to non-technical stakeholders

Knowledge, Skills, Abilities and Behaviors:

Knowledge of machine learning concepts, algorithms, and frameworks.
Knowledge of software engineering principles and best practices, such as version control, continuous integration, and agile development methodologies.
Strong understanding of data analysis and data manipulation techniques.
Ability to design and implement scalable, secure, and fault-tolerant ML Ops pipelines on AWS.
Ability to analyze and interpret data to identify patterns, trends, and anomalies, using advanced data manipulation techniques.
Outstanding communication skills (verbal, written, visualization, and listening).
Self-starter who can work independently as well as in a team setting.
Hands-on technologist with the ability to help drive the strategy and mentor others.
Giving and receiving effective feedback across all interactions.
Interest in understanding customer perspectives to aid in the development of the right solution.
Interest in understanding business needs to aid in developing solutions that are right for the broader organization.

Dice Id: 91132487
Position Id: 9076743
Posted 15 hours ago

Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Contact the job poster

Gaurav Verma

Recruiter @ Techgroup America Inc.

View Profile

Create job alert

Never miss an opportunity! Create an alert based on the job you applied for.

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