Machine Learning Engineer

TheTalentos; Atlanta (GA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Relocation assistance: Limited

Job summary

Next Data Labs in Atlanta, GA is seeking a driven Machine Learning Engineer to scale the ML life-cycle within the business insurance domain. You will be a full-stack ML engineer, building inference APIs, data enrichment services, and model monitoring while partnering with marketing, growth, and engineering teams.

You will empower data scientists, deploy models in the cloud using Docker/Kubernetes, and apply software engineering best practices like TDD and CI/CD to deliver robust ML solutions

Qualifications

• 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.)

Responsibilities

• 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.

Skills

Python

Django / Flask / FastAPI

SQL

Docker

Kubernetes

GitLab

Test-Driven Development

CI/CD

dbt

Airflow

Prefect

DVC

Tools

Docker

Kubernetes

GitLab

DBT

Airflow

Prefect

DVC

Job description

We are supporting a client in the Risk and Insurance industry in the search fora 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.

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 pipeline
• 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

Relocation assistance: Limited assistance