Dsnworldwide
Diversified Services Network, Inc. (DSN) is seeking a full-time Senior MLOps Software Engineer to join our team in Chicago, IL! We offer a HYBRID schedule, full benefits, PTO, 401k, and more! If you're looking to grow your technical career within an extremely reputable, stable Fortune 500 company - let's talk!
JOB RESPONSIBILITIES
Define scalable and secure architectures, frameworks and pipelines for building, deploying and diagnosing production ML applications
Enable users & teams on the ML platform; troubleshoot and debug user issues; maintain user-friendly documentation and training.
Collaborate with internal stakeholders to build a comprehensive MLOps Platform
Design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
Develop standards and examples to accelerate the productivity of data science teams.
Run code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift
Create way to automate the testing, validation, and deployment of data science models
Provide best practices and execute POC for automated and efficient MLOps at scale
EDUCATION & EXPERIENCE REQUIRED
Bachelors degree with 5+ years experience OR
Master’s degree with 3+ years experience
REQUIRED SKILLS
5+ years of experience working with an object-oriented programming language (Python, Golang, Java, C/C++ etc.)
Experience with MLOps frameworks like MLflow, Kubeflow, etc.
Proficiency in programming (Python, R, SQL)
Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
Strong understanding of DevOps principles and practices, CI/CD, etc. and tools (Git, GitHub, jFrog Artifactory, Azure DevOps, etc.)
Experience with containerization technologies like Docker and Kubernetes
Strong communication and collaboration skills
Ability to help work with a team to create User Stories and Tasks out of higher-level requirements.
DESIRED SKILLS
Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow.
Knowledge of inference systems like Seldon, Kubeflow, etc.
Knowledge of deploying applications and systems in Langfuse or Kubernetes using Helm and Helmfile.
Knowledge of infrastructure orchestration using CloudFormation or Terraform
Exposure to observability tools (such as Evidently AI)
SOFT SKILLS REQUIRED
Demonstrates a proactive, self-starting approach to work
Able to work independently with minimal supervision
BENEFITS
401(k)
Dental insurance
Vision Insurance
Disability insurance
Employee assistance program
Health insurance
Health savings account
Life insurance
Paid time off
Paid Holidays
#J-18808-Ljbffr
JOB RESPONSIBILITIES
Define scalable and secure architectures, frameworks and pipelines for building, deploying and diagnosing production ML applications
Enable users & teams on the ML platform; troubleshoot and debug user issues; maintain user-friendly documentation and training.
Collaborate with internal stakeholders to build a comprehensive MLOps Platform
Design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
Develop standards and examples to accelerate the productivity of data science teams.
Run code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift
Create way to automate the testing, validation, and deployment of data science models
Provide best practices and execute POC for automated and efficient MLOps at scale
EDUCATION & EXPERIENCE REQUIRED
Bachelors degree with 5+ years experience OR
Master’s degree with 3+ years experience
REQUIRED SKILLS
5+ years of experience working with an object-oriented programming language (Python, Golang, Java, C/C++ etc.)
Experience with MLOps frameworks like MLflow, Kubeflow, etc.
Proficiency in programming (Python, R, SQL)
Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
Strong understanding of DevOps principles and practices, CI/CD, etc. and tools (Git, GitHub, jFrog Artifactory, Azure DevOps, etc.)
Experience with containerization technologies like Docker and Kubernetes
Strong communication and collaboration skills
Ability to help work with a team to create User Stories and Tasks out of higher-level requirements.
DESIRED SKILLS
Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow.
Knowledge of inference systems like Seldon, Kubeflow, etc.
Knowledge of deploying applications and systems in Langfuse or Kubernetes using Helm and Helmfile.
Knowledge of infrastructure orchestration using CloudFormation or Terraform
Exposure to observability tools (such as Evidently AI)
SOFT SKILLS REQUIRED
Demonstrates a proactive, self-starting approach to work
Able to work independently with minimal supervision
BENEFITS
401(k)
Dental insurance
Vision Insurance
Disability insurance
Employee assistance program
Health insurance
Health savings account
Life insurance
Paid time off
Paid Holidays
#J-18808-Ljbffr