Applied ML Engineer: Enterprise Data Solutions

360 Technology LLC; Texas; On-site; USD 110,000 - 150,000; Full time

Job summary

360 Technology LLC is seeking a Machine Learning Engineer / Data Scientist to drive enterprise transformation across client portfolios. This role blends hands‑on delivery with clear communication in a consulting setting.

You will build models, notebooks, and pipelines to solve structured and unstructured data challenges, while collaborating with data engineers and business teams to ensure deployment readiness and business impact.

Qualifications

• Experience with Python, SQL, statistical modeling, ML libraries, and model evaluation practices.
• Working knowledge of data pipelines, experiment tracking, and production model handoff patterns.
• Comfortable connecting analytics work to business outcomes, risks, and adoption needs.

Responsibilities

• Develop models, notebooks, pipelines, and evaluation workflows for structured and unstructured data use cases.
• Work with data engineers and business teams to validate feature quality, model performance, and deployment readiness.
• Explain model behavior, assumptions, and tradeoffs to technical and non‑technical stakeholders.

Skills

Python

SQL

statistical modeling

machine learning libraries

model evaluation practices

Tools

Data pipelines

Experiment tracking

Production model handoff

Job description

Build practical machine learning solutions that turn enterprise data into predictions, recommendations, and measurable operating improvements.

360 Technology is looking for a Machine Learning Engineer / Data Scientist to support enterprise transformation programs across our client portfolio. This role is suited for someone who can combine hands-on delivery, clear communication, and practical problem-solving in a consulting environment.

What you will do

Responsibilities

Develop models, notebooks, pipelines, and evaluation workflows for structured and unstructured data use cases.

Work with data engineers and business teams to validate feature quality, model performance, and deployment readiness.

Explain model behavior, assumptions, and tradeoffs to technical and non-technical stakeholders.

What you bring

Qualifications

Experience with Python, SQL, statistical modeling, machine learning libraries, and model evaluation practices.

Working knowledge of data pipelines, experiment tracking, and production model handoff patterns.

Comfortable connecting analytics work to business outcomes, risks, and adoption needs.

Role focus

Areas of impact

Let us build what is next

Interested in the Machine Learning Engineer / Data Scientist role?

Send your resume, preferred location, work authorization, and a short note about the kind of work you want to do next.