Software Engineer III

Responsibilities

Design, build, and maintain platform components for ML model development, training, deployment, and monitoring. Develop and maintain production data and feature pipelines that feed machine learning models. Build and manage AWS cloud infrastructure, including Databricks, EMR, ECS, and S3, for model training and serving. Automate model deployment, testing, and release processes within the SDLC and MLOps toolchain. Migrate legacy ML workloads to scalable cloud-native platforms with zero downtime. Monitor platform health and model-serving infrastructure and resolve performance and stability issues. Use enterprise-authorized AI-assisted development tools for coding, testing, troubleshooting, refactoring, and documentation while validating outputs. Collaborate with data scientists and model developers to translate requirements into reliable platform capabilities. Contribute to design decisions, technical deliverables, secure coding practices, and continuous improvement.

Requirements

Formal training or certification in software engineering and at least 3 years of applied experience. Hands-on experience building and maintaining production data or machine learning pipelines. Hands-on experience using enterprise-authorized AI-assisted software development tools and critically evaluating their outputs. Understanding of responsible AI use, data sensitivity, secure handling of inputs and outputs, resiliency, and security expectations. Proficiency in Python and experience with ML libraries and frameworks such as Pandas, NumPy, and Scikit-learn. Working knowledge of AWS and cloud-native development patterns. Practical experience with infrastructure-as-code and deployment automation; Terraform is preferred. Ability to work independently on platform problems with moderate oversight. Preferred qualifications include Databricks, MLOps practices, AWS certifications, RAG or GenAI/LLM integration patterns, Docker, ECS, Kubernetes, and big data processing frameworks such as Spark.

Benefits

Competitive total rewards and eligibility-based benefits, including health care coverage, on-site wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching. Eligible roles may include commission-based pay or discretionary incentive compensation; compensation details are provided during hiring. Equal opportunity employment, reasonable accommodations, and an emphasis on diversity and inclusion.