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Machine Learning Eng Python, Machine Learning, Docker and Kubernetes Atlanta, GA ref 30301

Skills: Python, Machine Learning, Docker and Kubernetes., ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.), SQL

Job description Job insights Screening questions Candidate pipeline

Experience level: Mid-senior Experience required: 4 Years Education level: Bachelor’s degree Job function: Information Technology Industry: Financial Services Compensation: View salary Total position: 1 Relocation assistance: Limited assistance Visa : Only US citizens and Greencard holders

Job Summary

We are looking 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 NEXT 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 exposing opportunities to create business value.

Work cross-functionally with marketing, engineering, product, senior management, and external partners.

What We Need:

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 pipelining

Experience with ML-oriented data pipelining tools (dbt, Airflow, Prefect, DVC, etc.)

Unstoppable Qualities:

Experience in the insurance industry (strong fintech/lending experience will also be considered)

Experience with GitLab