Machine Learning Engineer, AI Engineer – Cloud Focus

career.io

full-time

Posted on: 10/16/2025

Location Type: Remote

Location: Remote • 🇱🇹 Lithuania

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💰 €3,000 - €5,000 per month

Mid-LevelSenior

Amazon RedshiftAWSCloudDockerKubernetesPythonPyTorchTensorflow

About the role

Develop, train, and deploy ML models using AWS SageMaker and other cloud-based frameworks.
Build and maintain SageMaker Pipelines for end-to-end workflows.
Design and operate real-time and batch inference environments using SageMaker Endpoints and EKS, including autoscaling, canary testing, and rollback mechanisms.
Develop retrieval-augmented generation (RAG) and large language model (LLM) pipelines, including retrieval systems, vector stores, prompt management, guardrails, and offline/online evaluation.
Create modular, reusable AI components for integration into production systems.
Implement ML governance practices such as versioning, reproducibility, dataset and model documentation, and privacy/export-control compliance.
Collaborate with data engineering, product, and cloud infrastructure teams to ensure efficient data flow and model integration.

Proficiency in Python and related ML/AI libraries.
Experience with AWS SageMaker Studio, Projects, Pipelines, Experiments, Debugger, and Clarify.
Experience with PyTorch and/or TensorFlow.
Familiarity with MLflow or similar experiment-tracking tools.
Strong knowledge of Docker and Kubernetes (K8s) for model packaging and deployment.
Experience building data pipelines with Redshift or Aurora.
Ability to integrate models with downstream APIs and production systems.
Hands-on experience with OpenSearch k-NN, pgvector, embedding generation, and chunking strategies.
Familiarity with prompt-evaluation and observability frameworks for LLMs.
Strong problem-solving and debugging skills.
Ability to work cross-functionally in fast-paced, collaborative environments.
Detail-oriented, with a focus on reliability, scalability, and maintainability.
Willingness and readiness to travel as required by project or client needs is expected.

Benefits

Learning opportunities with compensated certificates, learning lunches, and language lessons.
Chance to switch projects after one year.
Team building twice a year.
Office in Vilnius, Lithuania that offers themed lunches and a pet-friendly environment.
Remote work opportunities.
Flexible time off depending on a project.
Seasonal activities with colleagues.
Additional health insurance and loyalty days for Lithuanian residents.
Referral bonuses.
Recognition of important occasions of your life.