MLOps (and DevOps) Sr Lead / Architect

Hi Hope you are doing well. Role: MLOps (and DevOps) Sr Lead / Architect Location: Bellevue WA - Onsite 12 months contract Only W2, No C2C or Contract 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. Regards, Gaurav Sharma Sr Technical recruiter Direct : 781-896-2155 Email : gauravsyntricatetechnologies.com