26 to 50 of 1,097 Natural Language Processing Jobs

matter expert on a wide range of ML techniques and optimizations. Provides in-depth knowledge of ML algorithms, frameworks, and techniques. Enhances ML workflows through advanced proficiency in large language models (LLMs) and related techniques. Conducts experiments using latest ML technologies, analyzing results, tuning models Provides has Hands on coding to bring the experimental results into production solutions by … C/C++, etc. Intermediate Python is a must. Experience in applying data science, ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs) Hands-on experience with machine learning and deep learning methods. Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow. Experience … with Ray, MLFlow, and/or other distributed training frameworks. In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies. Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods. Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker More ❯

source data science tools and libraries. • Familiarity with AWS and related cloud technologies. • Experience with data governance and management best practices. • Knowledge of Natural Language Processing (NLP) is a plus. Technical Skills • Proficiency in Python and libraries such as Pandas, NumPy, and Scikit-learn. • Experience with machine learning frameworks like TensorFlow or PyTorch. • Strong SQL skills and … SageMaker). • Familiarity with tools like Jupyter, Snowflake, Docker, and Atlassian suite (Bitbucket, JIRA, Confluence). Soft Skills • Strong analytical and problem-solving abilities. • Excellent communication and teamwork skills. • Natural curiosity and a passion for uncovering insights from data. • Innovative mindset with attention to detail and time management Our commitment to inclusion PMI is on a continuous journey to More ❯

linking up with key stakeholders, managing projects, and spearheading R&D thinking. Desirable Skills: Experience in quant trading (especially eFX) or alpha research. Natural Language Processing (NLP) and Large Language Models (LLM) expertise. Familiarity with vector databases, SQL/NoSQL, and Amazon Bedrock. You may be assessed on the key critical skills relevant for this role More ❯

C/C++, etc. Intermediate Python skills are essential. Experience applying data science and ML techniques to solve business problems. Solid background in Natural Language Processing (NLP) and Large Models (LLMs). Hands-on experience with machine learning and deep learning methods. Deep understanding of deep learning frameworks such as PyTorch or TensorFlow. Experience with advanced ML More ❯

Problem-Solving Skills. Attention to Detail. Adaptability and Communication Skills. Patience and Persistence. Experience with advanced machine learning techniques such as deep learning, natural language processing (NLP), or reinforcement learning. Experience in using advanced features of cloud platforms (AWS, Azure, Google Cloud) such as machine learning services and automated data pipeline tools. Familiarity with big data frameworks More ❯

CA Mon-Fri: Core hours Salary: 120-150K Key Responsibilities: • Design, develop, and deploy ML and AI models to solve real-world problems • Fine-tune and apply Large Language Models (e.g., GPT, LLaMA, Claude) for natural language processing, summarization, classification, and generation tasks • Analyze large, complex datasets to identify trends, patterns, and actionable insights • Collaborate More ❯

business challenges and opportunities for AI-driven solutions. Design, develop, and deploy AI models and algorithms tailored to client needs. Provide technical expertise in AI technologies, including machine learning, natural language processing, and computer vision. Conduct data analysis and pre-processing to prepare datasets for AI model training. Implement AI models into production environments and optimize More ❯

AI: Stay abreast of the latest AI trends and Azure services. Evaluate new technologies - from Azure Cognitive Services and Azure OpenAI to emerging open-source frameworks for LLMs (Large Language Models) and RAG (Retrieval-Augmented Generation). Incorporate generative AI capabilities where relevant to enhance client solutions (e.g. intelligent document processing with GPT models). Cross-Project Impact … solutions at scale. A track record of delivering production-grade AI projects for enterprise clients is essential (this is a senior role and not suitable for junior candidates ). Language Skills: fluent in german and english Azure Expertise: Deep hands-on knowledge of Azure data and AI services - including Azure Machine Learning, Azure Databricks, Azure Data Lake/Synapse More ❯

end ML projects, from early experimentation to production deployment. Comfort with ambiguity, and the ability to shape, test, and validate product ideas in fast-moving environments. Deep expertise in NLP and GenAI, including Transformers, LLMs, RAG architectures, fine-tuning, and/or agent-based workflows. Hands-on experience with recommendation systems or search-based applications. Strong collaboration skills, with a … track record of working effectively across data science, engineering, product, and design. Experience processing and leveraging large, messy, unstructured datasets and making sense of them through ML. Excellent technical leadership, communication and mentorship skills, with the ability to bring others along on complex AI initiatives. Experience with modern software engineering and MLOps practices, including CI/CD, automated testing More ❯

ability to manipulate, query and visualise data and training/evaluation results (using e.g., Pandas, Matplotlib, Seaborn). Proven understanding of Information Extraction and Retrieval techniques. Proven understanding of NLP and large language models. Proven understanding of database concepts (differences between graph/relational/non-relational). Proven familiarity with cloud computing platforms (e.g., AWS, Azure, GCP), Azure More ❯

strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in standardizing our AI into … of some recognised AI and software leaders. · Experience in working with large datasets (> 1TB) · Able to implement production level coding practices, including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas … Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English) · Nice to have: Experience working on an agile software engineering team and working directly with Product Management teams; Azure Databricks, Microsoft Azure certification, Azure AI Fundamentals, Azure Data Scientist Associate Preferred Skills/Experience: · Demonstrates strong interpersonal, communication, and More ❯

strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in standardizing our AI into … of some recognised AI and software leaders. · Experience in working with large datasets (> 1TB) · Able to implement production level coding practices, including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas … Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English) · Nice to have: Experience working on an agile software engineering team and working directly with Product Management teams; Azure Databricks, Microsoft Azure certification, Azure AI Fundamentals, Azure Data Scientist Associate Preferred Skills/Experience: · Demonstrates strong interpersonal, communication, and More ❯

strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in standardizing our AI into … of some recognised AI and software leaders. · Experience in working with large datasets (> 1TB) · Able to implement production level coding practices, including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas … Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English) · Nice to have: Experience working on an agile software engineering team and working directly with Product Management teams; Azure Databricks, Microsoft Azure certification, Azure AI Fundamentals, Azure Data Scientist Associate Preferred Skills/Experience: · Demonstrates strong interpersonal, communication, and More ❯

on experience in developing and implementing AI and Data cloud solutions. Experience working with Azure AI services (or AWS, GCP) and AI model deployment. Understanding of generative AI, LLMs, NLP, and machine learning frameworks (TensorFlow, PyTorch, Hugging Face, etc.). Understanding of the AI application lifecycle, including application prototyping, productionising and monitoring. Python/Go/R. Problem solving skills. More ❯

foundations of Machine Learning algorithms Proficient in Python Have a deep knowledge of a sufficiently broad area of technical specialism (e.g. Time Series, Combinatorial Optimisation, Reinforcement Learning, Bayesian Statistics, NLP etc.) Good knowledge in mining large & complex data sets using SQL and Spark. Preferred Will be curious, enjoy problem solving and have empathy for the problems you are challenged with More ❯

data science to provide insight into the nature and structure of our data and content, both published content and internal data sets, and lead on developing models to improve processing, access, understanding and use of that data. Working closely with the Subject Matter Experts, Product Managers, Software Engineers and Product Designers, you will play a key role in improving … and line of business data and information. This will require working with structured and unstructured data, a large corpus of scholarly articles, using programmatic techniques such as statistical analysis, natural language processing, information retrieval, and machine learning. You will also work with the rest of the team to turn your insights and software prototypes into production services … and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to communicate complex technical findings clearly and effectively, both verbally and in writing More ❯

Qualifications: 4+ years of hands-on experience in AI/ML model development, including supervised and unsupervised learning, with a strong focus on Natural Language Processing (NLP) for unstructured data. 5+ years of proficiency in at least one analytical/statistical programming language (e.g., Python, R, Scala, Closure). 2+ years of experience manipulating and processing More ❯

new insights, enable analytics, gain efficiencies and automation. This role is based in an AI/ML team that is already working on projects involving Generative AI, Information Retrieval, NLP/NER/RE, document classification, and has won awards and recognition for its work. The team's future projects will be in diverse areas, such as regulatory, clinical, legal … Design and develop RAG based applications LLM fine-tuning, including preparation of training sets from internal data Agent-based applications Evaluating use-case specific LLMs AI/ML Engineering NLP: Named Entity Recognition across a variety of unstructured data Evaluating and training BERT-like models such as GLiNER, NuNER for NER tasks Analysing trade-offs between these models and LLMs … for NLP tasks Relationship Extraction: Evaluating different models for use-case specific RE, such as ATG Document and text Classification Data Engineering Designing and implementing data pipelines for model training and inference Building scalable data processing systems Optimizing data workflows and storage solutions Implementing robust ETL processes Evaluate and integrate new technologies and models Cross-team collaboration, identifying innovations More ❯

platforms like Tableau or Power BI. Understanding of machine learning concepts and algorithms (e.g. classification, clustering, regression). Interest in or experience with Natural Language Processing (NLP), Natural Language Generation (NLG), or Computer Vision. Awareness of enterprise graph technologies or network analysis techniques. Experience with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP More ❯

us is a desire to learn, a mastery of our discipline, strong mathematical and statistical skills, and software engineering prowess. We typically specialise in fields such as Computer Vision, Natural Language Processing and Deep Learning. Our Data Scientists are responsible for all aspects of the AI lifecycle, from understanding business problems, preparing training data, designing and building … You write production-grade, scalable Python code, ensuring that your models are robust, maintainable, and optimised for performance. Comfortable with PyTorch Knowledge of Transformer-based models Knowledge of Large Language Models (LLMs) Proven experience of having delivered successful Computer Vision or LLM projects into production Strong understanding of software development fundamentals, in particular deploying models to production and how … to set up pipelines. Demonstrate expertise in deep learning for computer vision, natural language processing, reinforcement learning etc. Displays in depth knowledge in machine learning best practices, scalable training and deployment, model introspection and evaluation Strong fundamentals in Mathematics, Statistics and Data Analysis Experience working in an Agile environment and knowledge of how Agile methodologies can be More ❯

businesses. Each project is different - one week, you might solve a data engineering challenge, which could involve mining large datasets. The next week, you may find yourself working on natural language processing using large language models, developing innovative AI applications. Contribute to cutting-edge research projects, advancing Compass Lexecon’s thought leadership in the application of … SQL and NoSQL databases (e.g. MongoDB) and Deep understanding and hands-on experience with a variety of data science tools and concepts, such as machine learning, causal inference, optimisation, natural language processing and computer vision Experience with cloud computing platforms (Azure, AWS, GCP) and containerization (Docker) Knowledge of data engineering principles such as data modelling, ETL processes More ❯

Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, such as Amazon AWS, Microsoft Azure, or Google Cloud Services. - Experience with deep learning, natural language processing, computer vision, or reinforcement learning. - Conveys highly technical concepts and information in written form to technical and non-technical audiences. - The ability to work on More ❯

functional collaboration—driving forward innovation while ensuring reliability, performance, and business value Responsibilities Architect and implement state-of-the-art machine learning solutions across use cases including intelligent document processing, risk modelling, and asset behaviour analytics Conduct advanced experimentation and model development, applying deep learning, LLMs, or probabilistic methods as appropriate Build high-performance, production-grade pipelines for data … on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and More ❯

functional collaboration—driving forward innovation while ensuring reliability, performance, and business value Responsibilities Architect and implement state-of-the-art machine learning solutions across use cases including intelligent document processing, risk modelling, and asset behaviour analytics Conduct advanced experimentation and model development, applying deep learning, LLMs, or probabilistic methods as appropriate Build high-performance, production-grade pipelines for data … on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and More ❯

science, as well as a passion for solving challenging problems. Responsibilities Essential Functions Model Development: Design, develop, and train machine learning and deep learning models for various applications, including natural language processing, computer vision, predictive analytics, and recommendation systems. Data Handling: Preprocess, analyze, and visualize large datasets to extract actionable insights; collaborate with data engineers to ensure … a production environment. Proficiency in programming languages such as Python, Java, or C++. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with data processing tools and platforms (e.g., SQL, Apache Spark, Hadoop). Knowledge of cloud computing services (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes) is a plus. Hugging More ❯