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ML/AI Engineer
Builds and deploys AI/ML models (focusing on speech recognition and legal insights) in production, optimizing performance, latency, and GPU usage while integrating LLMs and agentic workflows where applicable.
Senior Data Scientist
Build and deploy production-grade AI models using PyTorch and LLMs to power analytics from NielsenIQ’s global retail data, collaborating with engineers and business teams.
[Job-30912] AI-First Senior Software Engineer, Brazil
Build scalable cloud-native microservices in Java/Python on Azure, using AI tools like TensorFlow and PyTorch to automate engineering workflows and boost productivity.
Experienced Data Engineer Stockholm
Designs and builds scalable data pipelines and modern data platforms for public and private clients, using cloud-native tools and Python/SQL to enable analytics and AI workloads.
Experienced Data Engineer Malmö
Builds and maintains cloud-native data pipelines and platforms for public/private clients, enabling analytics and AI use cases with Python, SQL, and cloud services.
ML-инженер — RAG, LLM / VLM
ML engineer builds and optimizes RAG pipelines, fine-tunes VLM for technical docs, and prepares on-prem LLM/VLM inference for an AI platform serving engineers.
Yetakchi mutaxassis (Data Engineer)
Builds AI/ML solutions in Python, focusing on LLM, RAG, and AI agents, integrating them with backend systems and vector databases.
AI Engineer
Build and deploy generative AI solutions using RAG, prompt engineering, and frameworks like LangChain on Google Cloud or Azure.
Machine Learning Scientist, Pretraining
Research and develop large-scale deep learning models for biomolecular design, focusing on pretraining techniques in protein engineering using PyTorch or JAX.
Staff Machine Learning Engineer, ML Acceleration (Remote)
Lead a team to optimize and accelerate ML model training for autonomous vehicles, using PyTorch/JAX and distributed systems to cut development cycles and enable rapid hot-patching.
Machine Learning Engineer - Applied ML & Research
Build and deploy ML models for online gaming platforms, focusing on security, user experience, and data-driven decisions using Python, PyTorch, and SQL.
Senior Engineering Manager - Machine Learning
Leads a team of ML engineers and data scientists to design, deploy, and maintain machine learning systems for sports betting and gaming platforms using Python, TensorFlow/PyTorch, and AWS.
Staff Machine Learning Engineer - Applied ML & Research
Leads machine learning initiatives for an online gaming platform, designing and deploying scalable models to enhance security, user experience, and data-driven decisions for hundreds of thousands of users.
Data Scientist (LLM)
Build and deploy ML systems and LLM-powered features for a B2B wholesale marketplace, owning models from design through production monitoring.
Data Scientist (Economics)
Build pricing, forecasting, and recommendation models for a B2B wholesale marketplace using Python, SQL, and econometric techniques.
Praktikum im Bereich Data Science in der Fertigung (w/m/div.)
Praktikant:in entwickelt KI-Algorithmen für Qualitätskontrolle in der Serienproduktion, nutzt Python, TensorFlow/PyTorch und arbeitet mit Produktionsteams zusammen.
Internship Data Science in Manufacturing
Internship advancing machine-learning algorithms for quality assessment in series production using Python, PyTorch, and TensorFlow. You will build prototypes and support digitalization teams in manufacturing.
Senior Machine Learning Research Engineer - Research Engineering - MSR Cambridge
Builds and validates ML research prototypes (PyTorch) at scale, bridging academic research and product teams to deploy AI solutions for Microsoft’s global user base.
Middle / Senior Data Scientist (Финансы)
Build AI agents and ML models for bond trading: analyze order books, detect anomalies in payment flows, and generate trading signals using NLP and LLM techniques.
Senior ML Engineer [CICADA8]
Senior ML Engineer builds and fine-tunes LLM-based agents and RAG pipelines for cybersecurity vulnerability detection, deploying on-prem models and optimizing MLOps/LLMOps workflows.