Senior Machine Learning Engineer at Policygenius
Data Engineering at Policygenius...
Policygenius is on a mission to educate and right-size financial protection for everyone! This is a great opportunity to join our data engineering team as a Machine Learning Engineer to help advance our core MLOps capabilities. We are relentless in our grit and drive to reliably deliver outstanding products at scale while maintaining one of the best engineering cultures you’ll witness. We are growing fast, but we can go further faster with experienced, collaborative, challenge-seeking ML engineers like yourself.
Our data engineering team focuses on the company’s analytical data and ML pipelines/environments. This is delivered via product data engineers and supported by our data and ML infrastructure. As a senior data engineer focusing on ML deployment, you will be critical in developing and executing on our future roadmap for MLOps promoting the use of model repositories, ML pipelines, serialization, and feature stores to name a few. In this role you will work especially closely within the data team to ensure data scientists and engineers are able to, respectively, perform ML development and deployment at scale.
In this role, you will…
- Be responsible for designing, developing, and executing on a roadmap to ensure reliability and scalability of ML deployment
- Develop best practices and guidance to coach data scientists and engineers on ML pipeline development and deployment
- Collaborate closely in the design and development of ML-centric systems with stakeholders and data scientists while being acutely aware of deployment nuances
- Provide advice and support to the data team on a variety of technical ML workflows such as using model repositories, feature stores, elastic inference, hardware acceleration and distributed training
- Bring DevOps practices, tooling, and automation to our ML projects
- Act as a subject matter expert in handling a varying data formats such as visual/audio media and documents
Technologies to expect…
- General tooling
- Git, Terraform, Kubernetes, Docker, Spark
- You need to be familiar with most of these concepts and some of these tools
- Pipelining (Kubeflow, MLFlow, Spark ML, sklearn pipeline)
- Model repositories (SageMaker, MLFlow, DVC)
- Model serving (TF Serve, Cortex)
- Feature stores (Feast, Databricks feature store)
- Model serialization (MLFlow, ONNX)
- Distributed/Accelerated training/inference (spark, dask, CUDA)
- The data science stack (sklearn, pytorch, tensorflow, spark etc.), in particular the pipelining and serving side of these libraries
We’d love to hear from you if you…
- Have 4-6 years of relevant experience in data science and/or software engineering
- Obsess over automation and practical productionalization of machine learning models
- Enjoy working at the intersection of software engineering and data science
- Care more about deploying a model correctly and efficiently than training the best model
- Excel at solving machine learning problems via systems design and architecture
- Embrace a generative culture and excels in rapidly changing/evolving environments
- Have a bachelor’s degree in computer science or equivalent experience
You can expect...
- Company-paid health, dental, vision, life & disability insurance
- 401(k) plan, FSA & commuter benefits
- Generous PTO
- A flexible-first workplace, with the freedom to work in our beautiful offices or remotely as needed based on the needs of your role, team, and the business
- The opportunity to grow alongside a company shaking up a big, old-fashioned industry, including training, mentorship and coaching from leadership
- An inclusive community of fun, diverse, and open-minded coworkers committed to our mission of helping people get financial protection right
Policygenius is America's leading online insurance marketplace. We launched in 2014 and made our mark as an early insurtech pioneer. Our mission is to help people get financial protection right — and feel good about it — and we make it easy for our customers to understand their options, compare quotes, and buy insurance, all in one place. We’ve helped more than 30 million people shop for all types of insurance like they shop for everything else — online — and have placed over $60 billion in coverage. In early 2020, we announced our Series D funding round of $100 million, bringing our total funding to just over $150 million.
At Policygenius, we’re proud of building an environment that encourages our teammates to bring their authentic selves to work. Despite rapid growth (we’ve doubled in size year over year!), we’ve continuously maintained our inclusive culture through humility, hard-work, and humor, and we're looking for more people with grit, collaborative attitudes, and creative problem-solving skills to join our team. Come see why we’ve been voted one of Inc. Magazine's "Best Workplaces" four years in a row!
Diversity at Policygenius
Policygenius believes differences should be celebrated and is committed to building a team as diverse as the customers we serve. We welcome different perspectives and opinions to foster innovation, authenticity, and excellence across all parts of our company, and are committed to providing employees with a work environment free of discrimination and harassment.
As an Equal Opportunity Employer, Policygenius highly encourages applicants from all walks of life. All employment decisions at Policygenius are based on business needs, job requirements and individual qualifications without regard to actual or perceived race, color, sex, pregnancy, sexual orientation, gender identity or expression, age, national origin, political affiliation or belief, religion, disability, uniformed service, marital status or any other status protected by law.
Come join the team!