MLOps (and DevOps) Sr Lead / Architect

Highbrow LLC; Bellevue (WA); On-site; USD 180,000 - 240,000; Full time

Job summary

A telecommunications company based in Bellevue, WA is seeking an experienced MLOps (and DevOps) Sr Lead / Architect. This role involves designing and implementing MLOps workflows, collaborating with data scientists, and developing full stack solutions. Ideal candidates will have strong expertise in CI/CD practices, cloud platforms, and full stack development technologies. The position requires a blend of architecture responsibilities and hands-on development work, making it perfect for well-rounded tech professionals.

Qualifications

• Experience with MLOps and DevOps architectures is essential.
• Strong understanding of full stack development required.
• Experience with cloud platforms like AWS, Azure, or Google Cloud.
• Proficient in CI/CD and cloud platforms (AWS/Azure/GCP) with IaC (Terraform, CloudFormation).

Responsibilities

• Implement CI/CD pipelines for ML model deployment.
• Design MLOps workflows for model training and validation.
• Collaborate with data scientists to containerize ML models.
• Create scalable, secure, and reliable full-stack solutions with React/Angular/Vue and Node.js or Django.
• Monitor performance, diagnose issues, and optimize data pipelines and services.

Skills

MLOps architecture and implementation

DevOps practices

Full stack development

Cloud platforms expertise

CI/CD tools

Container orchestration

Data science and ML libraries

JavaScript/TypeScript

Tools

TensorFlow

Kubernetes

Terraform

Airflow

Seldon

TensorFlow Serving

Jenkins

GitLab CI

CircleCI

AWS

Azure

Google Cloud

Terraform

CloudFormation

Ansible

Chef

React

Angular

Vue.js

REST APIs

GraphQL

Microservices

Apache Spark

Kafka

Job description

Job Title :- MLOps (and DevOps) Sr Lead / Architect

Employment Type :- W2

Duration :- Long Term

Visa Type :- All Visa applicable which are ready for W2

Location- Bellevue, WA (Day-1 Onsite)

Industry :- Telecom

Job Description:

Need a strong candidate who has experience with MLOps (and DevOps) architecture and implementation experience and preferably understands Full stack development and was working as a full stack engineer in his previous roles.

MLOps:

• Familiarity with ML lifecycle tools (MLflow, DVC, Airflow) and version control for data and models.
• Experience with data science and ML libraries: TensorFlow, PyTorch, Scikit-Learn, etc.
• Knowledge of container orchestration with Kubernetes and model serving frameworks (e.g., Seldon, TensorFlow Serving).

DevOps:

• Proficient in CI/CD tools such as Jenkins, GitLab CI, or CircleCI.
• Cloud platforms expertise (AWS, Azure, Google Cloud) and cloud-native services (Docker, Kubernetes).
• Experience with IaC (Terraform, CloudFormation) and configuration management tools (Ansible, Chef).

Full Stack Development:

• JavaScript/TypeScript, HTML, CSS, and frameworks like React, Angular, or Vue.js.
• Experience with UI/UX design principles and responsive web design.
• Proficiency in Node.js, Python, or similar back-end technologies.
• Knowledge of RESTful APIs, GraphQL, and microservices architecture.

Nice-to-Have:

• Experience in Telco domain will be a huge plus but not mandatory
• Experience with data engineering tools (e.g., Apache Spark, Kafka).
• Knowledge of distributed computing and big data solutions.
• Prior experience with A/B testing, monitoring model performance, and tracking business metrics related to ML.

Job Responsibilities

Need a strong candidate who have experience with MLOps (and DevOps) architecture and implementation experience and preferably understands Full stack development and was working as a full stack engineer in his previous life.

MLOps:

• Implement CI/CD pipelines specifically tailored for machine learning model deployment.
• Design and develop MLOps workflows, including model training, validation, deployment, monitoring, and retraining.
• Collaborate with data scientists to containerize ML models and ensure efficient deployment to production.
• Utilize ML monitoring tools and frameworks (e.g., MLflow, Kubeflow, Airflow) to monitor model drift, performance, and data quality in production environments.
• Manage model versioning, artifact tracking, and reproducibility of experiments.

DevOps:

• Implement and manage CI/CD pipelines to automate code deployment and delivery.
• Design infrastructure as code (IaC) using tools like Terraform, CloudFormation, or Ansible.
• Deploy and manage cloud resources in AWS, Azure, or Google Cloud.
• Monitor system performance and optimize applications for reliability and performance.

Full Stack Development:

• Has experience Designing and implementing scalable and efficient front-end and back-end solutions.
• Build user-friendly web interfaces and responsive applications using frameworks like React, Angular, or Vue.js.
• Develop back-end APIs and services using Node.js, Django, or similar technologies.
• Ensure optimized performance, security, and scalability of web applications.