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Machine Learning Engineer (NLP / Deep Learning)

Precision Technologies

Location

Texas, United States

Salary

Not specified

Type

fulltime

Posted

Today

via linkedin

Job Description

Job Title: Machine Learning Engineer (NLP / Deep Learning)

Location: Remote

Job Type: Full-Time

Eligibility: H4 EAD / L2S / GC / USC / TN only

Note: No C2C / No consultancy resumes

Summary:

A fast-growing AI-driven technology company is hiring a full-time Machine Learning Engineer to join their expanding engineering team. This organization builds advanced machine learning platforms and data-driven products that help companies unlock insights, automate decision making, and deliver intelligent applications at scale. In this role, you'll work with technologies such as Python, machine learning frameworks, data pipelines, cloud infrastructure, and modern MLOps tooling to design and deploy production-ready ML models.

This is an exciting opportunity for someone who enjoys working at the intersection of data science, software engineering, and real-world product development. The team is looking for an engineer who can take machine learning solutions from concept to production while collaborating closely with data scientists and product teams. The biggest draw of this role is the chance to work on high-impact AI systems that directly influence product features and customer outcomes. You'll gain exposure to cutting-edge ML techniques, scalable data architectures, and a fast-paced environment where learning and growth are encouraged.

Required Skills \& Experience

  • Strong experience with Python and machine learning development
  • Experience building and deploying production machine learning models
  • Experience working with large datasets and data pipelines
  • Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or similar
  • Experience with cloud platforms and scalable data infrastructure
  • Strong understanding of software development best practices including testing and version control

Desired Skills \& Experience

  • Experience working with MLOps tools and model deployment pipelines
  • Experience building APIs for ML services
  • Experience working with distributed data processing systems
  • Experience deploying ML solutions in cloud environments

What You Will Be Doing

Tech Breakdown

  • 50% Python / Machine Learning Development
  • 30% Data Pipelines \& Model Training
  • 20% Cloud Infrastructure \& Model Deployment

Daily Responsibilities

  • 70% Hands On
  • 20% Team Collaboration
  • 10% Architecture \& Technical Planning

The Offer

  • Bonus eligible

You will receive the following benefits:

  • Medical, Dental, and Vision Insurance
  • Vacation Time
  • Stock Options

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