V

Version 1

Global digital transformation partner delivering outcomes

AI Engineer

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Strong proficiency in Python and SQL.
  • Experience with Scikit-learn, PyTorch and/or TensorFlow, Hugging Face, and major AI services from cloud service and model providers.
  • Experience with supervised and unsupervised learning, model evaluation, feature engineering, and statistical concepts.
  • Practical experience building retrieval-augmented generation (RAG) systems, AI agents, large language model-powered applications, and vector search solutions.
  • Familiarity with LangChain, LlamaIndex, Semantic Kernel, and LangGraph.
  • Experience with AWS, Docker and containerization, CI/CD pipelines, and DevOps practices.
  • Kubernetes experience is preferred.
  • At least 3 years of experience in machine learning engineering or data science, including deploying models to production and building generative AI applications involving RAG systems, large language model integration, or agentic workflows.
  • Demonstrated experience delivering AI solutions into production environments.

Responsibilities

  • Design, build, and maintain AI-powered applications and services.
  • Develop and deploy machine learning and generative AI solutions.
  • Build retrieval-augmented generation (RAG) systems and AI agents.
  • Integrate foundation models and application programming interfaces into enterprise applications.
  • Create reusable AI components and frameworks.
  • Train, fine-tune, evaluate, and deploy machine learning models.
  • Develop feature engineering and model evaluation pipelines.
  • Implement model monitoring and performance tracking.
  • Optimize model inference performance and cost efficiency.
  • Develop large language model-based applications and workflows.
  • Build prompt templates, agent frameworks, and orchestration pipelines.
  • Implement vector search and knowledge retrieval systems.
  • Design evaluation frameworks for AI quality, safety, and reliability.
  • Improve hallucination mitigation and response accuracy.
  • Design and automate machine learning model training, validation, and retraining pipelines.
  • Version and manage datasets, features, and model artifacts using MLflow or similar tools.
  • Deploy and serve machine learning models via REST APIs or batch inference at scale on Databricks, Snowflake, or similar platforms.
  • Monitor production model performance and detect drift and degradation.
  • Manage feature stores and ensure data pipeline reliability for machine learning workloads.
  • Implement experiment tracking and reproducibility across the model lifecycle.
  • Work closely with solution architects, product managers, and engineering teams.
  • Participate in code reviews and technical design discussions.
  • Support testing, deployment, and ongoing optimization activities.

Desired Qualifications

  • Kubernetes experience.

About the Company

Version 1

Global digital transformation partner delivering outcomes

Version 1 helps organizations transform digitally by adopting technology and driving innovation in a responsible way. It offers an end-to-end suite of services designed to tackle difficult challenges, leveraging the latest technologies and a team of world-class professionals to deliver real outcomes. What sets Version 1 apart is its clear focus on a balanced set of priorities: customer success, empowered people, and a strong, scalable organization, all backed by a large, globally distributed team (3,400+ people across 4 continents) delivering sustainable transformation. The company’s goal is to produce successful customer outcomes through sustainable, technology-driven transformation and responsible practices.

Company size
1,001-5,000
Company stage
Acquired
Total funding
$107.8M
Headquarters
Dublin, Ireland
Founded
1996

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