IT Software Engineer

2 days ago

New York United States, New York Nexiva Full-time $70 Permanent

need candidates with industries with aerospace, heavy equipment, automotive manufacturing, or industrial manufacturing.

Client: Caterpillar

Pay:$70/hr on C2C

Job Title - IT Software Engineer 3

Request #86512-1

Visa: GC& USC ( Need local)

Location: Chicago IL - Onsite 2-3 days a week/ no exceptions.

Duration: 12 months

Position's Contributions to Work Group:

  • The MLOps Platform Team works within the Enterprise Data and Analytics Organization at Caterpillar.
  • Driving the ability to work with Internal Teams to be able to support the full life-cycle of AI and machine learning development through to beyond production.
  • Helping build a platform that enables data driven decisions across the enterprise, helping teams build high-value data and AI/ML products, and enable the operationalization and reliability of all models.
  • We are searching for a driven and highly skilled MLOps Engineer to join our MLOps Platform team at ServiceNow.
  • The role will build the MLOps Platform, build self-service ML Development tooling, and building platform adoption.

Education & Experience Required:

  • Bachelors degree with 8+ years experience
  • Master's degree with 6+ years experience

Required Technical Skills

(Required)

  • 8+ 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.

Nice to Have:

  • 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 ClodFormation or Terraform
  • Exposure to observability tools (such as Evidently AI)

Soft Skills

(Required)

  • Someone who takes the initiative on their own
  • Someone who does not need to be micromanaged.

Typical task breakdown:

  • 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

Interaction with team:

  • Working with core team, maybe work with additional teams when needed.
  • Internal only position
  • Working with engineers and scrum team.

Work environment:

  • Onsite 2-3 days a week/ no exceptions.

Disqualifiers/Red Flags/Overqualifications:

  • Choppy tenure/ consistent job hopping.
  • Candidates have close to 20 years' experience, they will be overqualified.

Potential red flag, if the candidate is looking to manage or used to managing a team, the WD is looking for someone who can contribute to the effort and not necessarily run the effort.