- Company Name
- SEEKR
- Job Title
- AI Engineer
- Job Description
-
**Job title**
AI Engineer
**Role Summary**
Design, develop, and deploy large language model (LLM) components for a commercial product. Work in a fast‑paced, startup environment with a focus on experimentation, iterative improvement, and delivering AI‑driven features that meet customer needs.
**Expectations**
- Deliver production‑ready AI solutions on schedule.
- Drive continuous improvement of model accuracy, latency, and cost efficiency.
- Collaborate with product, data science, and operations teams to align AI capabilities with business goals.
- Participate in code reviews, documentation, and knowledge sharing.
- Operate in a hybrid work setting with remote flexibility.
**Key Responsibilities**
- Build and maintain LLM pipelines (data ingestion, preprocessing, fine‑tuning, inference).
- Fine‑tune, evaluate, and optimize large language models on proprietary data.
- Design and implement APIs, microservices, and deployment workflows for AI features.
- Monitor and troubleshoot model performance, latency, and run‑time costs.
- Experiment with prompt engineering, hyper‑parameter tuning, and architectural variations.
- Integrate AI components into the broader product stack and CI/CD pipelines.
- Ensure compliance with data privacy, security, and AI ethics guidelines.
- Communicate results to stakeholders and translate business requirements into technical solutions.
**Required Skills**
- Strong programming in Python with experience in PyTorch, TensorFlow, or Hugging Face Transformers.
- Proven commercial experience building LLM‑based products or services.
- Expertise in ML/AI operations: Docker, Kubernetes, CI/CD, and cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
- Familiarity with data pipelines, ETL, streaming inference, and real‑time performance monitoring.
- Ability to conduct prompt engineering, hyper‑parameter optimization, and model compression.
- Proficiency in unit testing, automated testing, and continuous integration.
- Excellent problem‑solving, debugging, and cross‑functional communication skills.
- Understanding of AI ethics, bias mitigation, and data privacy best practices.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related discipline.
- Optional certifications: AWS Certified Machine Learning – Specialty, Google Cloud Professional Machine Learning Engineer, Azure AI Engineer Associate, or equivalent.
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