Machine Learning Engineer
4 weeks ago
About the job Machine Learning Engineer
We are supporting a client in the Risk and Insurance industry in the search for a driven Machine Learning Engineer to help us bring software development rigor to the ML life-cycle within the business insurance industry. As an experienced innovator partnering with the marketing and growth teams, this is a massive opportunity to drive high growth impact at a hyper-growth startup. Your job is to be a full-stack ML engineer, supercharging all aspects of scaling Machine Learning at NEXT: application design and architecture, scalable deployment of inference solutions as APIs, data enrichment as a service, and model monitoring.
You will be joining an innovative division of based in Atlanta: Data Labs. The mandate of Data Labs is to build software and data solutions that meaningfully impact marketing, funnel, risk, and servicing/claims experiences.
What You'll Do:
- Empower our team of data scientists to rapidly develop and deploy ML solutions.
- Leverage software engineering best practices to create and deploy data-intensive and machine learning inference products.
- Understand the data and dig deep to extract actionable insights.
- Think creatively and outside the box to answer desired experimental questions as well as expose opportunities to create business value.
- Work cross-functionally with marketing, engineering, product, senior management, and external partners.
- 3+ years of hands-on experience in the complete software development life-cycle with demonstrated professional experience with machine learning
- Strong command of Python and the standard web development frameworks (e.g. Django, Flask, FastAPI) & fluency with database technologies, SQL, and Python data packages
- Demonstrated experience deploying models and applications to a cloud environment using tools like Docker and Kubernetes.
- Demonstrated experience with software engineering best practices, such as Test-Driven Development and continuous integration/deployment pipeline
- Experience with ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.)
- Experience in the insurance industry (strong fintech/lending experience will also be considered)
- Experience with GitLab
Relocation assistance: Limited assistance
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