Data Scientist (Deep Learning, NLP, LLMs)

PulseRise Technologies; A distancia; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

A leading tech company is looking for a highly skilled Machine Learning Engineer specializing in Deep Learning and Natural Language Processing. The ideal candidate will design and build ML models and pipelines for production readiness, focusing on NLP and Large Language Models. This remote position requires expert knowledge in PyTorch, TensorFlow, and MLOps tools. The role offers an opportunity to contribute to cutting-edge AI solutions in a collaborative environment.

Formación

• 5+ years in machine learning, with 3+ focused on deep learning/NLP.
• Strong expertise in MLOps tools like MLflow and Kubeflow.
• Hands-on with LLMs for fine-tuning and prompt engineering.

Responsabilidades

• Design and optimize ML models with a focus on NLP and LLM applications.
• Build scalable pipelines for model training and deployment.
• Work with data engineers to prepare large datasets.

Conocimientos

Deep Learning

Natural Language Processing (NLP)

Large Language Models (LLMs)

Python

MLOps Tools

Problem-Solving

Educación

Advanced degree in Computer Science or related field

Herramientas

PyTorch

TensorFlow

Hugging Face Transformers

NumPy

Pandas

Scikit-learn

Descripción del empleo

We are seeking a highly skilled Machine Learning Engineer with expertise in Deep Learning, Natural Language Processing (NLP), and Large Language Models (LLMs). You will be responsible for designing, building, and deploying advanced ML models and pipelines, ensuring scalability, performance, and production readiness. The ideal candidate has strong research knowledge combined with hands‑on engineering skills to deliver intelligent, enterprise‑grade AI solutions.

Details

• Location: Remote in EU
• Employment Type: Full-Time, B2B Contract
• Start Date: ASAP
• Language Requirements: Fluent English

Key Responsibilities

• Design, develop, and optimize ML models with a focus on deep learning, NLP, and LLM-based applications.
• Build scalable pipelines for training, fine‑tuning, evaluation, and deployment of models.
• Work with frameworks such as PyTorch, TensorFlow, and Hugging Face Transformers.
• Fine‑tune and adapt pre‑trained LLMs (GPT, BERT, LLaMA, etc.) for domain‑specific tasks.
• Develop solutions for text classification, summarization, embeddings, RAG, and conversational AI.
• Ensure model scalability, robustness, and low‑latency performance in production environments.
• Collaborate with data engineers to prepare and optimize large‑scale datasets.
• Implement MLOps practices (CI/CD, monitoring, retraining, governance).
• Participate in code reviews, documentation, and technical knowledge sharing.

Requirements

• 5+ years of experience in machine learning, with at least 3+ years focused on deep learning/NLP.
• Strong expertise in PyTorch or TensorFlow, and NLP frameworks (Hugging Face, spaCy, NLTK).
• Hands‑on experience with LLMs (GPT, T5, LLaMA, Falcon, etc.), fine‑tuning and prompt engineering.
• Proficiency in Python and libraries (NumPy, Pandas, Scikit‑learn).
• Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML).
• Strong understanding of transformer architectures, embeddings, and attention mechanisms.
• Familiarity with cloud platforms (AWS, Azure, GCP) for ML deployment.
• Excellent problem‑solving and debugging skills.

Nice to Have

• Experience with vector databases (Pinecone, Weaviate, Milvus) for semantic search.
• Knowledge of retrieval‑augmented generation (RAG) pipelines.
• Exposure to multimodal ML (text + image/audio/video).
• Contributions to open‑source ML/NLP projects.
• Advanced degree (MSc/PhD) in Computer Science, AI, or related field.
• Industry background in fintech, healthcare, telecom, or e‑commerce.