Implement and optimize production-ready analytics code, maintain Python repositories, research data sources, build predictive models, and collaborate with teams.
About the Role:
You will be part of the Converge Engineering team, reporting to the Head of Engineering.
You’ll be implementing and optimizing innovative production ready analytics code as well as maintaining Python repositories and building tests.
Responsibilities:
- Transform specs into efficient, production ready python code as part of an agile 3 week sprint development process
- Explore new data-sources and their applicability to the Converge platform
- Extract and create data to productionize theoretical models and analytics components
- Research and build predictive models for the probability of cyber attack, and other data driven applications in the platform
- Analyze data and derive insights
- Continuously maintain, test and improve models and provide concise reporting of results
- Create and orchestrate microservices via Airflow and Docker containers
- Continuously test and deploy microservices via CI / CD
- Refactor, unit-test, and maintain Python codebase
- Work with different team members and stakeholders representing all areas of the business
- Regularly prepare and present content to stakeholders within Converge
- Assist with platform development more broadly when required
Qualifications:
- 5+ years professional experience in ML Engineering or related field (Data Science, AI, Modeling, etc.) using Python
- BS in Computer Science or relevant field
- Competency in ML python packages such as Pandas, NumPy, PySpark, scikit-learn, Anaconda, TensorFlow, etc.
- Proficiency with feature stores, Graph databases, SQL, NoSQL, Data Lakes and other data storage technologies
- Experience with data visualization tools
- Applied statistics skills, such as regression, explainability, distributions, and statistical testing
- Understanding of standard machine learning algorithms and graphical modeling, and having successfully applied several in the correct context
- Proficient understanding of version control best practices using Git
- Prolonged periods sitting at a desk and working on a computer.
- Ability to lift up to 15 pounds occasionally.
- Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.
- Pay Range: $135,000 – $185,000 annually (commensurate with experience and location).
- Total Compensation Context: This role may be eligible for annual performance bonuses and equity participation.
- Benefits Overview: Converge provides comprehensive health benefits (medical, dental, vision), a 401(k) plan with employer contribution, and flexible paid time off (PTO).
Converge Insurance is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Employment decisions are made without regard to race, color, religion, sex (including pregnancy, gender identity, or sexual orientation), national origin, age, disability, veteran status, or any other legally protected characteristic.
Top Skills
Airflow
Anaconda
Docker
NoSQL
Numpy
Pandas
Pyspark
Python
Scikit-Learn
SQL
TensorFlow
Similar Jobs
Healthtech • Software
The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.
Top Skills:
PythonPyTorch
Big Data • Fintech • Mobile • Payments • Financial Services
As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.
Top Skills:
KubeflowMlflowPythonPyTorchRaySparkXgboost
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
As a Staff Machine Learning Engineer, you will design and implement infrastructure and platform features for AI workloads, collaborate with teams, improve SRE practices, and mentor colleagues.
Top Skills:
AnsibleDockerGitlab CiGoHelmJ2EeJavaKubernetesLinuxNvidia GpusPrometheusPythonSplunk
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine



