MACHINE LEARNING ENGINEER / AI ENGINEER (CLOUD FOCUS)

ABOUT THE COMPANY

LITIT, a joint venture between NTT DATA and Reiz Tech, is a company with deep-rooted industry know-how, dedicated to innovation within the IT sector. Its primary focus is delivering high-quality solutions in the DACH region. With a commitment to excellence, LITIT combines the best of German precision, Japanese work ethics, and Lithuanian talent to provide unparalleled IT service and support to its clients.

ABOUT THE CLIENT

Our client is a globally renowned company in the premium automotive industry, distinguished by a long-standing tradition of excellence in design and engineering. For decades, they have been at the forefront of performance innovation, while also driving progress in sustainability and electrification. With a presence in over 100 markets, they continue to inspire a dedicated global community and set benchmarks for luxury, innovation, and mobility of the future.

ABOUT THE ROLE

We are looking for a Machine Learning Engineer to design, build, and deploy advanced ML and generative AI solutions on AWS SageMaker and other cloud platforms. You will be responsible for developing scalable machine learning systems from model training to deployment while implementing best practices for reproducibility, governance, and continuous improvement.

RESPONSIBILITIES

• 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.

REQUIREMENTS

• 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. This may include occasional domestic or international travel, sometimes on short notice.

Nice to have:

• Experience with other cloud platforms such as Azure ML or GCP Vertex AI.

• Knowledge of security and compliance standards for data handling and AI systems.
  

WHAT WE OFFER

• 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.