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Senior ML Engineer

Remote:

Full Remote

Contract:

Full time

Experience:

Senior (5-10 years)

Work from:

United States

Offer summary

Qualifications:

5+ years of engineering experience in ML applications, Hands-on experience with ML frameworks like TensorFlow and PyTorch, Proficient in CI/CD processes and cloud management, Experience deploying LLMs in production environments, Familiarity with backend frameworks and containers.

Key responsabilities:

Design, develop, and deploy ML systems
Integrate ML functionalities into product stack
Ensure reliability, scalability, and operational efficiency

Intetics Information Technology & Services SME https://intetics.com/

501 - 1000 Employees

See more Intetics offers

Job description

Intetics Inc, a leading global technology company providing custom software application development, distributed professional teams, software product quality assessment, and “all-things-digital” solutions, is seeking a talented Senior ML Engineer to join our team.

About the Project: Innovative AI marketplace. From scratch, you'll be the first developer.

About the Role

We are seeking a highly skilled Senior ML Engineer to join our dynamic team at Intetics Inc. The ideal candidate has a robust background in Machine Learning, DevOps practices, and hands-on experience with Large Language Model (LLM)-based solutions. In this role, you will play a critical role in designing, developing, and deploying complex systems that leverage state-of-the-art ML techniques and language models. You'll work cross-functionally to integrate ML-driven functionalities seamlessly within our product stack, ensuring reliability, scalability, and operational efficiency.

Requirements

Experience: 5+ years of engineering experience, with a focus on ML applications.
Hands-on experience with ML frameworks (TensorFlow, PyTorch) and knowledge of model training, evaluation, and deployment.

Proficient in creating CI/CD pipelines, infrastructure as code (e.g., Terraform, Ansible), and cloud platform management (AWS, GCP, Azure).

Demonstrated experience working with LLMs (e.g., GPT, Llama) for application in production environments.

Backend frameworks (Node.js, Django or Flask).
Experience with Code Assistants (Github Copilot, Codex, etc.).

Strong expertise in cloud services, containerization (Docker, Kubernetes), and microservices architecture.

Will be a Plus:
Data Science Background: Experience with data analysis, statistical modeling, and familiarity with data science tools (e.g., Pandas, NumPy, Scikit-learn).
Experience in NLP and conversational AI.
Proficiency with frontend technologies (React, Angular, Vue)
Familiarity with RESTful APIs and GraphQL.
Understanding of data engineering principles and tools for handling large datasets.
Exposure to A/B testing, experiment design, and metrics-driven development.