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.