About the AI Engineer role
An AI Engineer designs, builds, and deploys artificial intelligence systems: machine learning models, large language model applications, and the data pipelines that feed them. Unlike research-focused roles, AI engineers are measured on working software. They turn models into reliable products that run in production and improve with real usage.
The role sits between data science and software engineering. A strong AI engineer writes production-quality code, understands model behavior well enough to debug it, and knows how to evaluate whether a system is actually good before shipping it. In many teams, they also integrate third-party foundation models and build the guardrails, evaluation suites, and monitoring around them.
Be explicit in your posting about the problems the engineer will work on, your ML stack, and whether the role leans toward training models, building LLM-powered features, or MLOps infrastructure. The AI field is broad, and precise scope attracts precisely matched candidates.
AI Engineer job description template
Job brief
We are looking for an AI Engineer to build and deploy machine learning solutions that power our products. You will work with our engineering and product teams to design AI systems, develop and fine-tune models, build data pipelines, and take features from prototype to production. To succeed in this role, you should have strong programming skills, hands-on experience with modern machine learning frameworks, and a pragmatic approach to shipping AI features that create real value for users.
Responsibilities
- Design, build, and deploy machine learning models and AI-powered features into production
- Develop and maintain data pipelines for training, evaluation, and inference
- Integrate and fine-tune large language models and other foundation models where appropriate
- Build evaluation frameworks to measure model quality, safety, and regression before release
- Monitor production AI systems and improve their accuracy, latency, and cost over time
- Collaborate with product managers and designers to scope AI features that solve user problems
- Write clean, tested, production-quality code and participate in code reviews
- Stay current with AI research and tooling, and evaluate new techniques for practical use
- Document systems, experiments, and decisions so the team can build on your work
Requirements and skills
- Proven experience as an AI Engineer, Machine Learning Engineer, or in a similar role
- Strong programming skills in Python and experience with software engineering best practices
- Hands-on experience with machine learning frameworks such as PyTorch or TensorFlow
- Experience deploying and operating models in production, including APIs and batch pipelines
- Understanding of data structures, data modeling, and SQL
- Familiarity with LLM application patterns such as retrieval-augmented generation, prompting, and fine-tuning
- Ability to communicate technical trade-offs clearly to non-technical stakeholders
- BSc or MSc in Computer Science, Engineering, Mathematics, or equivalent practical experience
Nice to have
- Experience with cloud ML platforms such as AWS SageMaker, Google Vertex AI, or Azure ML
- Experience with MLOps tooling for experiment tracking, model registries, and CI/CD
- Contributions to open-source ML projects or published applied research
- Experience with vector databases, embeddings, and semantic search
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