Job ID: JOB_ID_1026
Position Summary
Appian Infotech Inc is currently seeking a seasoned Senior MLOps Engineer for a long-term project based in Chicago, IL. This is an onsite role requiring local candidates who can contribute to the development and scaling of our machine learning infrastructure. The ideal candidate will have over a decade of experience in software engineering with a specialized focus on the intersection of Machine Learning and DevOps. You will be instrumental in building, deploying, and monitoring production-grade ML pipelines that drive core business value. This role demands a high level of technical expertise in containerization, cloud orchestration, and automated model lifecycle management.
Core Responsibilities
- Design, build, and maintain scalable MLOps pipelines using frameworks such as MLflow and Kubeflow to automate the machine learning lifecycle.
- Develop and optimize production-level code in Python, Golang, or Java, ensuring high performance and reliability of ML services.
- Architect and implement cloud-native solutions on AWS, leveraging services like SageMaker, EKS, and Lambda for model deployment.
- Establish and manage robust CI/CD pipelines for machine learning models, integrating automated testing, versioning, and deployment strategies.
- Utilize containerization technologies like Docker and Kubernetes to ensure consistent environments across development, staging, and production.
- Implement observability and monitoring tools (e.g., Evidently AI, Langfuse) to track model performance, data drift, and system health.
- Collaborate with Data Scientists to transition experimental models into scalable, production-ready inference systems.
- Manage infrastructure as code (IaC) using Terraform or CloudFormation to ensure reproducible and secure cloud environments.
- Lead the adoption of best practices in DevOps, including GitOps, security integration, and automated scaling.
Required Technical Skills
- 10+ years of experience in object-oriented programming (Python is mandatory; Golang or Java preferred).
- Deep expertise in MLOps frameworks (MLflow, Kubeflow, Seldon Core).
- Proficiency in SQL and R for data manipulation and analysis.
- Advanced knowledge of Kubernetes, including Helm and Helm File for application deployment.
- Strong background in DevOps tools such as GitHub Actions, Azure DevOps, and JFrog Artifactory.
- Experience with infrastructure orchestration and cloud security best practices.
Preferred Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience building model inference systems with advanced deployment methods (Canary, Blue/Green).
- Knowledge of LLM observability and evaluation frameworks.
- Proven ability to work in an agile environment and lead cross-functional technical initiatives.
Interview Process
- Initial screening with the recruitment team.
- First Round: Virtual technical interview focusing on coding and MLOps architecture.
- Second Round: In-person interview at the Chicago office for final technical and cultural assessment.
Special Requirements
Locals only; Onsite requirement; First round virtual; Second round in-person.
Compensation & Location
Salary: $185,000 – $245,000 per year
Location: Chicago, IL
Recruiter / Company – Contact Information
Recruiter / Employer: Appian Infotech Inc
Email: nirbhay.s@appianinfotech.com
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