AI, Engineer

AI in this role

pytorchtensorflowscikit-learn

prompt-engineeringml-opsai-safety

Master Works is seeking a skilled AI, Engineer to design, develop, and deploy artificial intelligence and machine learning solutions that solve real-world business problems. The ideal candidate has strong experience in machine learning, data engineering, and software development, and is comfortable taking models from research to production.

Key Responsibilities

Design, develop, and implement innovative solutions using AI technologies such as machine learning (ML), deep learning (DL), and big data analytics.

Develop and maintain end-to-end AI pipelines, from data collection and preprocessing to model training and deployment.

Analyze large and complex datasets using advanced techniques to provide actionable solutions.

Integrate AI solutions with existing systems to enhance efficiency and innovation.

Work with cross-functional teams to guide and train team members in AI-related fields.

Optimize model performance, scalability, and reliability in production environments.

Track and evaluate the performance of AI models to ensure continuous improvement.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field.

Experience with AI tools and technologies such as TensorFlow, PyTorch, and Scikit-learn.

Strong programming skills in Python.

In-depth knowledge of machine learning and deep learning algorithms.

Ability to work with big data and analyze it.

Familiarity with REST APIs, version control (Git), and software engineering best practices

Experience with MLOps, containerization, and deployment tools (Docker, Kubernetes, CI/CD pipelines).

Experience with large language models (LLMs), generative AI, or prompt engineering.

Understanding of data privacy, security, and responsible AI principles.

Job Location: Client Site

How we rate this

AI, Engineer at Master-Works rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringML OpsAI SafetyPyTorchTensorFlowscikit-learn

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How do you monitor a model once it's live, and how do you know it needs retraining?
How do you think about the risk of an AI system in this kind of role failing silently?
What's a project where you used PyTorch hands-on?
Walk me through how you've used TensorFlow in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Prompt Engineering, ML Ops, AI Safety, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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