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Ml Machine Learning Engineering

  • ... Posted on: Apr 17, 2026
  • ... Akaasa Technologies
  • ... St Paul Park, Minnesota
  • ... Salary: Not Available
  • ... Full-time

Ml Machine Learning Engineering   

Job Title :

Ml Machine Learning Engineering

Job Type :

Full-time

Job Location :

St Paul Park Minnesota United States

Remote :

No

Jobcon Logo Job Description :

Title: ML (Machine Learning) Engineering

Location: St. Paul, MN - Hybrid - 3 days a Week Onsite *** Local Candidates Only ***

Find someone who has current minnesota project

TECHNICAL SKILLS
Must Have

  • Advanced SQL
  • Amazon AWS Cloud
  • Amazon Bedrock
  • Amazon SageMaker
  • Apache Airflow
  • AWS EKS / Kubernetes
  • AWS Step Functions
  • Certified Python programmer
  • CI/CD deployment
  • DevOps pipeline experience related to the automation of application testing, delivery, and infrastructure as code (e.g., GitHub, Gradle, Puppet, Terraform, AWS CloudFormation)
  • Docker for AWS
  • MLOps

Qualifications:

  • Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
  • 5+ years of experience in a similar role in a production environment.
  • Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
  • Hands-on experience with cloud computing platforms such as AWS.
  • Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
  • Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, IBM MQ, Apache Kafka, etc.
  • Experience with iterative development processes, thriving in dynamic and agile environments.
  • Ability to own ML delivery tasks end-to-end with little to no direct support. Hands-on experience in deploying machine learning models into production environments.
  • Strong understanding of software design patterns, principles, architecture, and operations.
  • Strong communication skills and the ability to collaborate effectively with business partners, vendors, end users, and cross-functional teams.

Jobcon Logo Position Details

Posted:

Apr 17, 2026

Reference Number:

27496-20508

Employment:

Full-time

Salary:

Not Available

City:

St Paul Park

Job Origin:

CIEPAL_ORGANIC_FEED

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Title: ML (Machine Learning) Engineering

Location: St. Paul, MN - Hybrid - 3 days a Week Onsite *** Local Candidates Only ***

Find someone who has current minnesota project

TECHNICAL SKILLS
Must Have

  • Advanced SQL
  • Amazon AWS Cloud
  • Amazon Bedrock
  • Amazon SageMaker
  • Apache Airflow
  • AWS EKS / Kubernetes
  • AWS Step Functions
  • Certified Python programmer
  • CI/CD deployment
  • DevOps pipeline experience related to the automation of application testing, delivery, and infrastructure as code (e.g., GitHub, Gradle, Puppet, Terraform, AWS CloudFormation)
  • Docker for AWS
  • MLOps

Qualifications:

  • Advanced degree (Master's or Ph.D.) or equivalent industry experience in Computer Science, Machine Learning, or related fields.
  • 5+ years of experience in a similar role in a production environment.
  • Experience working with large scale datasets and building ETL pipelines using Spark, Kubeflow, StreamSets, etc.
  • Hands-on experience with cloud computing platforms such as AWS.
  • Strong proficiency in Python and experience with NLP techniques, resources, and methodologies such as Scikit-learn, TensorFlow, PyTorch, HuggingFace, Comprehend, XGBoost, LangChain, etc.
  • Experience integrating machine learning models and data-driven algorithms into larger system architectures that involve pieces like Flask, ElasticSearch, PostgreSQL, IBM MQ, Apache Kafka, etc.
  • Experience with iterative development processes, thriving in dynamic and agile environments.
  • Ability to own ML delivery tasks end-to-end with little to no direct support. Hands-on experience in deploying machine learning models into production environments.
  • Strong understanding of software design patterns, principles, architecture, and operations.
  • Strong communication skills and the ability to collaborate effectively with business partners, vendors, end users, and cross-functional teams.

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