Must have

• Python

• Machine learning

• Docker

• Kubernetes

• GenAI

• LLM

• English

• Polish

Nice to have

• NoSQL

• GCP

Requirements description

You must have:

• a minimum of 4 years in a machine learning or AI engineering role, with hands-on experience in building and deploying models in production environments,
• strong programming skills in Python and experience with machine learning libraries and frameworks (e.g., PyTorch, TensorFlow),
• experience with Generative AI and Large Language Models (LLMs),
• proficiency in designing and implementing model evaluation and experimentation frameworks,
• familiarity with cloud platforms (preferably GCP) and containerization tools (Docker, Kubernetes) for model deployment,
• experience with version control and model lifecycle management tools,
• effective communication skills for both technical and non-technical stakeholders,
• analytical skills to understand and tackle complex modeling and deployment challenges.

Offer description

deepsense.ai is seeking a skilled Machine Learning Engineer [Senior] to join our team, focusing on developing and deploying AI-driven solutions. In this role, you’ll work alongside our data engineers and scientists to build scalable systems that address complex challenges across various industries. Your contributions will span the full lifecycle of AI development, from initial design to final deployment, emphasizing innovative and impactful solutions.

Your responsibilities

1. design, develop, and integrate machine learning models into end-to-end pipelines for real-world applications,
2. build and manage multi-model pipelines, integrating in-house models and third-party APIs,
3. collaborate with MLOps engineers on deployment, model packaging, versioning, and production integration,
4. fine-tune and optimize Generative AI and LLMs for custom applications, ensuring high performance and scalability,
5. implement model evaluation pipelines for continuous monitoring, logging, and retraining,
6. translate complex business needs into project requirements, system architecture and development plans,

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