and iterate on models and algorithms while taking ownership of the entire lifecycle, from idea inception to robust deployment and operationalization. Stay at the forefront of research in IR, NLP, and Generative AI, incorporating relevant innovations into practical, impactful solutions. Represent Bloomberg at industry events, scientific conferences, and within open-source communities. Qualifications Proven practical experience solving real-world problems … using NLP, Information Retrieval, Search technologies, and Generative AI technologies. Knowledge of search platforms like Apache Solr or Elasticsearch is a plus. Significant industry experience or a relevant academic background (such as an MSc or PhD in Computer Science, Machine Learning, Mathematics, Statistics, or Engineering). We value practical ability and a demonstrated track record of delivering impactful results over More ❯
leadership team. As Associate Director of Artificial Intelligence, you'll drive and execute the company's AI strategy - leading initiatives that harness the power of Machine Learning, Generative AI, NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to … field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines More ❯
leadership team. As Associate Director of Artificial Intelligence, you'll drive and execute the company's AI strategy-leading initiatives that harness the power of Machine Learning, Generative AI, NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to … field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines More ❯
leadership team. As Associate Director of Artificial Intelligence, you'll drive and execute the company's AI strategy-leading initiatives that harness the power of Machine Learning, Generative AI, NLP, and more to fuel scalable business growth and operational excellence. Role Scope Lead the identification of opportunities and risks in a fast-evolving competitive landscape, using AI/ML to … field (degree or equivalent experience). Hands-on experience developing and deploying production-grade ML models, including advanced RAG (retrieval-augmented generation) systems. Deep expertise in Generative AI, LLMs, NLP, and Knowledge Graphs-with a track record of translating complex models into real-world business solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines More ❯
month contract on a hybrid basis based near Stratford, London. Main Accountabilities: Design and implementation of tooling and technologies to support Machine Learning and the use of Large Language Models Take ownership of the design, deployment, and maintenance of machine learning models Recommend, implement, and use tooling to improve the development, operations, and observability of machine learning models, large … language models, and AI-related services Essential skills: Previous experience working on online Chat or Chatbors, particular voice, is a must-have. Strong recent hands-on capabilities in Python are a must-have. Experience with a microservice environment using tools such as Jupyter, Pandas, Numpy, Fast API, and SQL alchemy is a must. Srong's understanding of deploying and … and its applications is a must-have Desireable : Any of Terraform, Helm, Kubernetes, Postgres would be advantageous. Qualifications or demonstrable experience in Data Science and Machine Learning including algorithms, NLP, XAI. A demonstrable experience in delivering real-world applications using Generative AI, in particular Large Language Models. The two-stage remote interview process with the capacity to start ASAP. More ❯
Chelmsford, Essex, South East, United Kingdom Hybrid / WFH Options
Stott & May Professional Search Limited
Senior Research Scientist - AI/ML & Signal Processing Location: Great Baddow (Hybrid, 2 days onsite per week) Salary: Up to £70,000 + benefits We are seeking a Senior Research Scientist to join a growing Data and Decision Support capability within a leading global technology and defence organisation. This role is focused on developing novel AI/ML algorithms … and statistical signal processing techniques , with applications across sectors including space, defence, security, and commercial industries. You'll work at the forefront of innovation, applying advanced machine learning and data science techniques to time-series, sensor and sequential data , delivering high … impact research, prototypes, and demonstrators. You'll also collaborate with academic partners and multidisciplinary teams working across areas such as radar, sonar, RF, distributed sensing, reinforcement learning, computer vision, NLP, and generative AI. Key Responsibilities Lead delivery of technical research projects, mentoring junior researchers. Develop prototypes, proof-of-concepts, and novel inference algorithms. Produce technical reports, proposals, and present findings More ❯
Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques. Scientific publication track record at top-tier AI/ML/NLP conferences or journals PREFERRED QUALIFICATIONS Demonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customization Experience with model optimization techniques (quantization, distillation, compression, inference optimization etc.) Experience with More ❯
using FastAPI framework and how different it is from Flask? Data engineering What are best practices in pre-processing textual content during ingestion phase? Any experience of using NLP algorithms for pre-processing raw text content? Docker/Kubernetes What are few proven docker images inspection methods? Any experience of popular known deployment methods on k8s cluster? Gitops More ❯
Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience. Bioinformatics expertise, familiarity with large scale bioinformatics datasets. Experience using Nextflow pipelines. Knowledge of NLP techniques and experience of processing unstructured data, using vector stores, and approximate retrieval. Familiarity with orchestration tooling (e.g. Airflow or Google Workflows). Experience with AI/ML powered More ❯
Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience. Bioinformatics expertise, familiarity with large scale bioinformatics datasets. Experience using Nextflow pipelines. Knowledge of NLP techniques and experience of processing unstructured data, using vector stores, and approximate retrieval. Familiarity with orchestration tooling (e.g. Airflow or Google Workflows). Experience with AI/ML powered More ❯
Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience. Bioinformatics expertise, familiarity with large scale bioinformatics datasets. Experience using Nextflow pipelines. Knowledge of NLP techniques and experience of processing unstructured data, using vector stores, and approximate retrieval. Familiarity with orchestration tooling (e.g. Airflow or Google Workflows). Experience with AI/ML powered More ❯
model pipelines Test and Validate services. Deploy and monitor solutions for impact Work within a cross-functional application team to build scalable language services in the range of NLP, NLU, and NLG for live SaaS products Help develop and groom an experiment backlog Build models that solve real-world problems Optimize models for production throughput and uptime requirements Automate … deployments, testing, and monitoring (MLOps) Requirements 5+ years of developing data & analytics products like sentiment analyzers, translation engines, summarizers, or other language services Expert in Machine Learning, Modeling, and development with Python Expert in MLOps with at least one platform, e.g.: MLflow, Kubeflow, or end-to-end automation with SageMaker services Ability to mentor others and work independently Nice More ❯
Development & Innovation: Identify and implement opportunities where AI can create tangible value for customers. Design and develop production-grade AI solutions that automate complex tasks. Build and optimize advanced NLP models for document analysis and interpretation. Contribute to finding the right ML framing of industry challenges. Create scalable AI systems that can handle diverse requirements across different markets. Technical Leadership … and infrastructure best practices, with a focus on the ML software development lifecycle. Expertise in building, fine-tuning, and optimizing Large Language Models (LLMs), transformer architectures, and advanced NLP systems using frameworks like Hugging Face and OpenAI SDKs. Strong background in modern deep learning techniques, LLMs, and data-intensive applications. Familiarity with state-of-the-art agentic AI frameworks More ❯
JAX or similar frameworks Preferred Qualifications Experience in building AI agents (based on RL, LLMs, etc.) Experience in building multi-agent simulation Background in Large Language Models/NLP and Multi-modal deep learning Exposure to projects integrating human sciences (e.g. sociology, behavioural, cognitive, neuroscience) Familiarity with spatial analysis algorithms (e.g. space syntax) Learn More About Autodesk Welcome to More ❯
distributed computing, high- performance computing Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies Scientific publication track record at top-tier AI/ML/NLP conferences or journals PREFERRED QUALIFICATIONS 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques. Demonstrated More ❯
distributed computing, high- performance computing Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies Scientific publication track record at top-tier AI/ML/NLP conferences or journals PREFERRED QUALIFICATIONS 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques. Demonstrated More ❯
leverage the modern heterogeneous computing environment which includes our revolutionary computing chips. Work closely with Machine Learning Scientists to develop and productize novel machine learning algorithms for computer vision, NLP, and recommendation applications. Work with the Field Engineering team to understand real world customer scenarios and provide guidance on model architecture and implementations that take advantage of our hardware. Understand … analyze, and exploit the interplay between machine learning accelerator software and hardware, including data preprocessing, streaming, batching, quantization, adaptors, and distributed workloads for Large Language Model (LLMs.) Create Lightmatter-specific tools that can interoperate between Machine Learning ML frameworks. Minimum Requirements Masters degree in Computer Science, Machine Learning, or related discipline, or foreign degree equivalent, plus four (4) years More ❯
allow our customers to personalise messages across all digital touchpoints. This includes working with multi-modal data such as images, text, and more, leveraging cutting-edge technologies including Large Language Models (LLMs). This is an exciting opportunity at the forefront of machine learning, helping to bring Accessible Intelligence to our customers with great scope to make a key … Analyse performance and continuously improve scoring processes for hosted models. Best Bits of the Job Exposure to a phenomenal array of machine learning domains, including massive-scale search, ranking, NLP, hybridization, classification, multi-modal data processing (images, text, etc.), and far beyond. Leveraging state-of-the-art technologies, including Large Language Models (LLMs), to enhance our products and … services. Fully real-time architecture for data processing, model development, and deployment. Deploying and enhancing ML frameworks, optimizing for inference, and training/retraining cycles. Online testing for models with live data using proprietary A/B/N testing technology to rapidly determine what works (and what doesn't). A super-bright, supportive, and friendly machine learning More ❯
Git/GitHub and continuous deployment workflows. Preferred Skills Experience with Docker and multi-container application architecture. Backend development using FastAPI . Knowledge of AI/ML techniques , especially NLP and language models. Experience with Kubernetes and Google Kubernetes Engine (GKE) . Exposure to frontend development (e.g., React ) is a plus. Please apply with your updated CV if this More ❯
Description Support for NLP project to accurately and automatically tokenize language data with spoken or written origins; develop automated solutions for the annotation of language data with parts of speech information, and improved existing models by scoring performance against human-generated annotations for speech and text. Requirements Clearance Required Top Secret SCI w/Full Polygraph Bachelor's … skill areas: Foundations: Mathematical, Computational, Statistical Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment More ❯
make faster, smarter decisions and better serve their clients and constituents. The Information Enrichment & Content Generation (IECG) Team builds scalable ML solutions for two key areas: Information Enrichment: Traditional NLP use-cases such as Named Entity Recognition/Disambiguation, classification, topical modeling etc. Content Generation: Generative use-cases such as Summarization, Drafting new documents, Generating legal insights, on-point recommendation … legal contracts, analyzing the congressional budget along with government's actual spending and generating insights to support tax positions. To solve these, we apply a range of ML/NLP techniques including statistical models, deep neural networks, language models & third-party generative LLMs. We work closely with product managers, software engineers and domain experts in an agile environment. In … our clients' needs. You will collaborate with product managers and domain experts to understand business problems and translate those into appropriate ML problems. You will research groundbreaking ML/NLP techniques and apply them to our business problems. You will collaborate with domain experts to gain valuable insights and use their expertise to get high quality annotated training data. You More ❯
data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience. Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen). Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products. Some More ❯
data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience. Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen). Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products. Some More ❯
data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience. Knowledge of AI/ML approaches and deployment of AI/ML powered applications – especially using language models or NLP and agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen). Knowledge of AI/ML evaluation and benchmarking approaches, experience with iterative improvement of AI/ML models and products. Some More ❯
