Staff Software Engineer, EvolutionIQ
ML Platform
$230-250k
+Stock options
More information about location
AI for insurance carriers
Job no longer available
AI for insurance carriers
101-200 employees
Job no longer available
$230-250k
+Stock options
More information about location
101-200 employees
Company mission
To transform the insurance industry through a partnership between AI and human experts, ultimately making it more fair and affordable for everyone.
Role
Who you are
- 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
- Exudes our ambitious, collaborative, and empathetic values
- 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
- 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
What the job involves
- 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
- 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
- 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
Our take
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.
The company's offering is certainly an attractive one for businesses handling large volumes of these claims - the solutions aim to help insurance providers detect and prevent fraud without impacting their productivity and customer experience. Historically, the insurance industry has had access to vast amounts of data without optimizing how they use it. EvolutionIQ's machine learning algorithms harness the learnings from every data point, allowing for much more well-informed, actionable insights.
Competition is steep among AI insurance firms, and EvolutionIQ counts rivals such as CCC Intelligent Solutions and Riskcovry in this space. However, the market size is huge and ripe for disruption. With a valuation of more than $200 million following a successful VC funding round, EvolutionIQ is focused on the further development of its product and international expansion as it hopes to capture a larger slice of this $10 billion market.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 5 rounds)
Aug 2024
$20.2m
LATE VC
Jun 2023
$10.3m
LATE VC
Total funding: $60.4m
Company benefits
- 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
Company values
- Make complex things simple
- Make business strong
- Create more value
- Make Data-Driven Decisions
Company HQ
Flatiron District, New York, NY
Articles
Leadership
Tomas Vykruta
(CEO)Has founded a number of companies including Electrolab Inc, and was a Senior Software Development Engineer at Microsoft ATG. Joined Waymo's Machine Learning wing, and then worked as a Staff Engineer at Google. Is currently one of Google's Developer Experts.
Michael Saltzman
(COO)Studied Engineering and Economics at Dartmouth, and obtained an MBA from Stanford. Co-founded Roomie Rentals while still a student, and then joined Bridgewater Associates as an Investment Associate.
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