AI/ML Engineer

This is a fully remote position, open to applicants in United Kingdom, +5 more countries.

📋 Description

• Design, implement, and sustain effective AI and machine learning pipelines for both internal and client-focused initiatives.

• Deploy, oversee, and enhance AI models, including pre-trained models, LLMs, and custom ML models, within production settings.

• Collaborate with data scientists to transition model prototypes into scalable, production-grade AI systems.

• Enhance and fine-tune model performance, latency, and cost-effectiveness on cloud platforms.

• Integrate AI/ML solutions with AWS, GCP, and Azure services.

• Utilize Docker and Kubernetes for uniform deployment processes.

• Employ MLOps methodologies encompassing CI/CD, model versioning, continuous monitoring, and maintenance.

• Collaborate with software engineering teams to embed AI functionalities into applications and user workflows.

• Keep abreast of developments in AI/ML, Generative AI, and MLOps deployment techniques.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative discipline.

• 4 to 5 years of progressive experience in machine learning engineering, software development with a focus on ML/AI, or a similar position.

• 1–3 years of experience with ADK or other agentic frameworks.

• Proficient programming skills in Python.

• Expertise in TensorFlow, PyTorch, or Scikit-learn.

• Practical experience deploying and utilizing pre-trained models such as LLMs or comparable Generative AI technologies in production environments.

• Familiarity with AWS, GCP, and Azure platforms.

• Experience using Docker and Kubernetes.

• Comprehensive understanding of data engineering principles and ETL/ELT procedures.

• Experience with version control systems like Git.

• Experience orchestrating machine learning pipelines with Kubeflow or managed cloud services.

• Proven experience in building and optimizing scalable AI/ML systems.

• Knowledge of MLOps best practices, model monitoring, logging, and CI/CD pipelines for AI assets.

• Strong communication and teamwork abilities.

• Capacity to work effectively across cross-functional teams, including solution architects and data scientists.

• Successful candidates must meet the requirements necessary for a background check.

🏝️ Benefits

• Competitive total rewards package.

• Flexible remote work options with no daily travel to an office.

• Significant training allowance.

• Professional development days.

• Opportunities for training and certification.

• Laptop with the choice of operating system.

• Annual budget to customize your work environment.

• Annual wellness budget.

• Paid vacation days.

• Paid sick days.

• A day off to volunteer for a charity of your choice.