Staff Software Engineer, EvolutionIQ

• Exudes our ambitious, collaborative, and empathetic values
• Hold yourself to high standards, ensuring high quality and passion for the field in which you operate
• Remain agile and move between rapid prototyping and stable production development
• Write design documents, perform code reviews, and maintain state of the art engineering practices
• Open to giving and receiving critical feedback
• Believes in the mission of the company, cares about fundamental fairness
• Enthusiasm for team work and pair work
• Kind, empathetic, polite, and professional
• Utilizes data and metrics to drive decision-making, ensuring that the ML platform is optimized for performance, reliability, and scalability
• Proactively identifies and addresses bottlenecks in the ML pipeline, leveraging their expertise to develop and implement innovative solutions that enhance productivity and performance
• 8+ years of software development experience with a focus on platform development with AI/ML applications of scale
• Experience in providing technical leadership to ML Infra / ML Platform teams
• Experience in shipping products at scale
• Expertise in clean and efficient coding with a focus on Python
• Experience with orchestration frameworks such as Dagster/Airflow
• Expertise in one or more Cloud platforms (GCP preferred but not required)
• Bachelor’s Degree or higher in Computer Science, Mathematics, or related field
• Excellent document writing skills (additional to presenting results through Jupyter notebooks)
• Extreme creativity and resourcefulness, appetite to solve previously unsolved problems

• We are seeking a highly skilled and motivated Staff Software Engineer - ML Platform to lead the architecture, deployment, and scaling of our machine learning (ML) and artificial intelligence (AI) infrastructure
• This role combines deep technical expertise with strategic impact to drive innovation in the ML pipeline, optimize end-to-end workflows, and ensure robust deployment in production environments
• As a Staff ML Platform Engineer, you will collaborate closely with machine learning engineers and senior leadership to streamline experimentation, improve model observability, and enhance overall system performance
• You’ll play a pivotal role in setting the MLOps standards across the organization
• Design, build, and launch scalable ML and data processing systems supporting multi-machine data processing (e.g., MapReduce), GPU/TPU model training, and automated model monitoring systems on cloud platforms
• Automate model lifecycle management, including training, evaluation, and deployment, to enable fast, safe, and consistent updates across environments
• Introduce modern, scalable frameworks for model monitoring, feature engineering, hyperparameter tuning, and continuous re-training, ensuring robust model performance over time
• Lead the deployment of models through REST and gRPC APIs, enabling smooth integration with application frontends and real-time user interaction
• Continuously research, evaluate, and implement the latest MLOps tools, frameworks, and platforms to improve efficiency, scalability, and reliability of ML operations
• Implement and manage monitoring systems to track model and data performance, proactively identifying and mitigating issues using tools like Prometheus and Grafana
• Apply best practices in secure data handling and model integrity within ML workflows, ensuring regulatory and security compliance norms
• Share MLOps knowledge and improvements in ML engineering workflows through internal training sessions and presentations
• Support the next phase of ML pipeline development, focusing on building, maintaining, and monitoring pipelines to handle 10-100x increases in data volume

• Premium Medical Insurance Plan – Empire Blue Cross Blue Shield Medical insurance
• 401K with employer matching
• Dental Coverage – Principal Financial
• Life insurance / ACDC coverage – Reliance Standard
• Vision – Reliance Standard
• Short Term and Long Term Disability – Unum
• Employee stock option plan
• $500 to get you started setting up your home office and $200 every year for upgrades after that

Total funding: $60.4m

EvolutionIQ is a data-driven claim guidance platform for insurance providers. Its products combine structured and unstructured claim data with external third party data to provide powerful claim guidance, in an attempt to modernize the claims operations process.