201 to 225 of 389 Permanent Deep Learning Jobs

startup with the reach of a global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to build and deploy machine learning systems that accelerate decision-making and unlock business value. You’ll design, implement and deploy production-grade AI and ML systems, ranging from NLP pipelines that extract insights from … who want to see their models not just trained, but deployed, adopted, and driving measurable results. What You’ll Do Design and deliver AI systems: Build and deploy machine learning models and data-driven products that directly impact investment decisions and portfolio company performance. Drive measurable impact: Partner with internal desks and portfolio teams to integrate ML products into … cloud platforms, and MLOps best practices to build scalable, reusable solutions. Communicate insights clearly: Distill complex technical findings into concise, actionable narratives for technical and business audiences alike. Keep learning and pushing boundaries: Expand your engineering toolkit across the full ML development lifecycle—from prototyping to deployment—and explore new architectures, tools, and approaches to solving complex, real-world More ❯

startup with the reach of a global investment platform. Our team partners directly with internal investment desks as well as portfolio companies across industries to build and deploy machine learning systems that accelerate decision-making and unlock business value. You’ll design, implement and deploy production-grade AI and ML systems, ranging from NLP pipelines that extract insights from … who want to see their models not just trained, but deployed, adopted, and driving measurable results. What You’ll Do Design and deliver AI systems: Build and deploy machine learning models and data-driven products that directly impact investment decisions and portfolio company performance. Drive measurable impact: Partner with internal desks and portfolio teams to integrate ML products into … cloud platforms, and MLOps best practices to build scalable, reusable solutions. Communicate insights clearly: Distill complex technical findings into concise, actionable narratives for technical and business audiences alike. Keep learning and pushing boundaries: Expand your engineering toolkit across the full ML development lifecycle—from prototyping to deployment—and explore new architectures, tools, and approaches to solving complex, real-world More ❯

AI Engineer (Machine Learning Expertise) Reporting to: Engineering Manager Office Environment: Hybrid (minimum two days per week) Type: Full time, Permanent SC Eligibility Required Joining Our Mission Shape the future. Make an impact. At QuantSpark, pioneering the strategic application of data, analytics, and AI is at the heart of our work. We empower businesses and government to thrive, not … optimisation. SaaS & Manufacturing: Driving technological transformation and efficiency across verticals. The Role In this role, you'll be responsible for designing, developing, and maintaining scalable AI systems using machine learning and data-driven approaches. You'll integrate ML models into production-ready AI solutions while collaborating closely with data scientists, software engineers, and product teams. Monitor and optimise model … strong programming and software engineering skills, especially in Python, and follow best practices like version control and scalable code design. You bring practical experience designing, training, and evaluating machine learning models, including deep learning and statistical optimisation. You are proficient in developing data pipelines for large, complex datasets using Python, SQL, NoSQL, and big data tools, preferably More ❯

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 models, and deploying them into production. … from you. Apply now and help shape the future of claims automation. Responsibilities Develop features for our state-of-the-art claims automation platform Research, build and deploy machine learning algorithms and models to production within product teams Provide technical guidance and input on the design and implementation of machine learning algorithms Support with customer PoVs and onboarding … product requirements and help translate these into technical solutions Execute and deliver full AI/ML solutions from sourcing training data, design and implementing state-of-the-art machine learning models, testing, benchmark and product-driven research for model performance improvement, to shipping stable, tested, performant code in an agile environment. Work closely with Product Managers to help shape More ❯

interest in generating real-world impact with industrial applications. Must have: Relevant PhD degree in a STEM field (e.g., engineering, physics, mathematics, computer science). Evidence of self-motivated learning, listening, creative problem solving, critical thinking and solutions communication. We are less interested in specific technologies and tools, and more interested in your attitude, learning speed and thought … scripting. Ability to deal with ambiguity and change, in a high-growth environment, while maintaining high standards of quality and attention to detail. Bonus: Existing interest in standard machine learning and deep-learning packages (e.g., scikit-learn, Keras, PyTorch). Exposure to commercial engineering tools or optimisation packages (e.g., Dassault Systèmes, Siemens, ANSYS, Aspen), open-source optimisation More ❯

What's the opportunity? Intercom's Machine Learning team is responsible for defining new ML features, researching appropriate algorithms and technologies, and rapidly getting first prototypes in our customers' hands. We are an extremely product focussed team. We work in partnership with Product and Design functions of teams we support. Our team's dedicated ML product engineers enable us … to move to production fast, often shipping to beta in weeks after a successful offline test. We are very passionate about applying machine learning technology, and have productized everything from classic supervised models, to cutting-edge unsupervised clustering algorithms, to novel applications of transformer neural networks. We test and measure the real customer impact of each model we deploy. … Plan, measure & socialize learnings to inform iteration Partner deeply with the rest of team, and others, to build excellent ML products What skills might I need? Broad applied machine learning knowledge 3-5 years applied ML experience Practical stats knowledge (experiment design, dealing with confounding etc) Intermediate programming skills Strong communication skills, both within engineering teams and across disciplines. More ❯

Java Mathematical Modelling Mathematical skills, particularly a keen understanding of probabilities and statistics Analytic mindset Strong communication skills Accuracy and attention to detail Experience in data science (big data, deep learning, machine learning) is beneficial If you feel you have the skills and experience required for this opportunity, please contact Oliver Wilson at (url removed) Spectrum IT More ❯

London The Data Science function plays a pivotal role in delivering advanced Artificial Intelligence capabilities across the organisation. This position focuses on designing, developing, and deploying production-grade machine learning solutions while contributing to the strategic growth of AI-driven products. The successful candidate will join a multidisciplinary, globally distributed team and collaborate closely with Software Engineers, Product Managers … and other stakeholders. The role requires strong mathematical and statistical foundations, excellent software engineering skills, and proven expertise in modern machine learning techniques, including Computer Vision, Natural Language Processing, and Deep Learning. ---------------------------------------- Key Responsibilities Design, build, and deploy advanced machine learning models and algorithms into production. Lead technical development within cross-functional teams, providing guidance on ML … Models (LLMs). Demonstrated success delivering Computer Vision and/or NLP/LLM projects into production. Solid understanding of model deployment, pipelines, and software development fundamentals. Expertise in Deep Learning, including training, evaluation, and optimisation. Strong grounding in mathematics, statistics, and data analysis. Experience working in Agile environments. Familiarity with technologies such as AWS, GCP, Kubernetes, Ray More ❯

Machine Learning Engineer – On-Device Health Monitoring Cambridge (1 day a week) Up to £80,000 + Equity + Benefits About the Role We’re working with a pioneering health-tech start-up that’s transforming the way we measure human health through sound. Their mission is to create the world’s leading foundation model for turning sound into … health insights — enabling preventative health monitoring through devices people already own. They’re now looking for a Machine Learning Engineer to build and optimise on-device ML models for health and biosignal monitoring, helping take their technology from proof of concept to a production-ready product. You’ll be at the forefront of developing models that run efficiently on … hands-on technical role that offers full exposure to the early-stage startup experience — from prototyping and experimentation to strategic product decisions. Key Responsibilities Develop, optimise, and deploy machine learning models for on-device health monitoring. Experiment with architectures and apply techniques such as quantisation, pruning, and compression to improve efficiency. Collaborate with cross-functional teams to take research More ❯

Machine Learning Engineer – On-Device Health Monitoring Cambridge (1 day a week) Up to £80,000 + Equity + Benefits About the Role We’re working with a pioneering health-tech start-up that’s transforming the way we measure human health through sound. Their mission is to create the world’s leading foundation model for turning sound into … health insights — enabling preventative health monitoring through devices people already own. They’re now looking for a Machine Learning Engineer to build and optimise on-device ML models for health and biosignal monitoring, helping take their technology from proof of concept to a production-ready product. You’ll be at the forefront of developing models that run efficiently on … hands-on technical role that offers full exposure to the early-stage startup experience — from prototyping and experimentation to strategic product decisions. Key Responsibilities Develop, optimise, and deploy machine learning models for on-device health monitoring. Experiment with architectures and apply techniques such as quantisation, pruning, and compression to improve efficiency. Collaborate with cross-functional teams to take research More ❯

successful Head of Data Science should have: Proven experience in data science and analytics, ideally within the public sector or regulatory body. A strong background in statistical modelling, machine learning, and data visualisation tools Expert use of standard statistical tools e.g. R/Python and relevant associated libraries Deep expertise in building and maintaining AI and machine learning models, including use of deep learning, natural language processing, and LLMs Excellent leadership and team management skills. A solid understanding of data governance and ethical considerations. Outstanding communication skills to present complex data in an accessible manner. A degree or equivalent qualification in data science, mathematics, or a related field. Demonstrated ability to collaborate across departments and More ❯

the UK, 1 in Japan, and 1 in Seattle to build the future of advanced metal components. To do this it uses proprietary software packages which combine advanced machine learning and physical modelling to invent better alloys, devise better ways to process them, and design better 3D-printed components. Responsibilities Design, develop and validate novel machine learning models … optimize manufacturing processes and material composition Collaborate closely with process engineers, material scientists and other domain experts to identify and engineer the most meaningful features Develop Alloyed’s machine learning platforms to facilitate adoption and application of validated models Work as part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A More ❯

the UK, 1 in Japan, and 1 in Seattle to build the future of advanced metal components. To do this it uses proprietary software packages which combine advanced machine learning and physical modelling to invent better alloys, devise better ways to process them, and design better 3D-printed components. Responsibilities Design, develop and validate novel machine learning models … optimize manufacturing processes and material composition Collaborate closely with process engineers, material scientists and other domain experts to identify and engineer the most meaningful features Develop Alloyed’s machine learning platforms to facilitate adoption and application of validated models Work as part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A More ❯

the UK, 1 in Japan, and 1 in Seattle to build the future of advanced metal components. To do this it uses proprietary software packages which combine advanced machine learning and physical modelling to invent better alloys, devise better ways to process them, and design better 3D-printed components. Responsibilities Design, develop and validate novel machine learning models … optimize manufacturing processes and material composition Collaborate closely with process engineers, material scientists and other domain experts to identify and engineer the most meaningful features Develop Alloyed’s machine learning platforms to facilitate adoption and application of validated models Work as part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A More ❯

the UK, 1 in Japan, and 1 in Seattle to build the future of advanced metal components. To do this it uses proprietary software packages which combine advanced machine learning and physical modelling to invent better alloys, devise better ways to process them, and design better 3D-printed components. Responsibilities Design, develop and validate novel machine learning models … optimize manufacturing processes and material composition Collaborate closely with process engineers, material scientists and other domain experts to identify and engineer the most meaningful features Develop Alloyed’s machine learning platforms to facilitate adoption and application of validated models Work as part of a fast-paced, agile development team Identify and prioritize opportunities to rapidly deliver new capabilities Build … and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker) A More ❯

Machine Learning Engineer (Up to £180K) – Top VC-Backed Stealth Startup London (Hybrid working) Are you ready to drive the next big leap in AI? We’re working with a stealth-mode startup—backed by top venture capitalists—on a mission to make AI more accessible than ever. Their groundbreaking solutions are redefining how industries leverage intelligent systems, accelerating … functionally in a fast-paced environment where your ideas can shape the future of AI. What We’re Looking For Seasoned ML Expertise: 3+ years of hands-on machine learning experience, with a track record of executing end-to-end ML projects. Deep Tech Know-How: Strong background in ML, Deep Learning, LLMs, and frameworks like More ❯

Machine Learning Engineer (Up to £180K) – Top VC-Backed Stealth Startup London (Hybrid working) Are you ready to drive the next big leap in AI? We’re working with a stealth-mode startup—backed by top venture capitalists—on a mission to make AI more accessible than ever. Their groundbreaking solutions are redefining how industries leverage intelligent systems, accelerating … functionally in a fast-paced environment where your ideas can shape the future of AI. What We’re Looking For Seasoned ML Expertise: 3+ years of hands-on machine learning experience, with a track record of executing end-to-end ML projects. Deep Tech Know-How: Strong background in ML, Deep Learning, LLMs, and frameworks like More ❯

Machine Learning Engineer (Up to £180K) – Top VC-Backed Stealth Startup London (Hybrid working) Are you ready to drive the next big leap in AI? We’re working with a stealth-mode startup—backed by top venture capitalists—on a mission to make AI more accessible than ever. Their groundbreaking solutions are redefining how industries leverage intelligent systems, accelerating … functionally in a fast-paced environment where your ideas can shape the future of AI. What We’re Looking For Seasoned ML Expertise: 3+ years of hands-on machine learning experience, with a track record of executing end-to-end ML projects. Deep Tech Know-How: Strong background in ML, Deep Learning, LLMs, and frameworks like More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

/ML instrumentation to extract insights and optimize the product experience. Provide strategic product guidance through data-driven recommendations, experimentation insights, and root cause analyses. Build and scale machine learning algorithms and pipelines to production using big data technologies. Develop and deploy retrieval-augmented generation (RAG) systems and LLM-based applications. Design and evaluate A/B tests and … up to date with industry advancements in data processing and AI/ML, and introduce best practices into the organization. Requirements 7+ years of experience in data science, machine learning, and AI development across structured and unstructured data. Advanced degree (Master’s or PhD) in Computer Science, Engineering, Mathematics, Statistics, or a related field (preferred) Deep experience in … personalization, search, or recommendation systems (3–4 years in a product-focused environment). Expertise in deep learning architectures (e.g., attention models, transformers, retrieval models). Hands-on experience with LLMs and GenAI technologies. Strong programming and problem-solving skills with proficiency in Python, SQL, Spark, and Hive. Deep understanding of classical and modern ML techniques, A More ❯

We’re hiring a creative & driven Machine Learning Engineer to help us redefine digital experiences at the intersection of fashion, generative AI, and computer graphics. You will be a key member of our high-energy R&D team, responsible for designing, building, and deploying the cutting-edge models that will power the next generation of e-commerce and entertainment. … Responsibilities: Design, train, and deploy a range of machine learning models, with a focus on generative AI and computer vision. Collaborate closely with researchers to productionise and prototype novel solutions for consumer facing use cases at scale. Develop and maintain robust, scalable machine learning pipelines for data processing, training, and inference. Optimise models and algorithms for performance to … handle large, multimodal datasets. Stay at the forefront of ML & AI research, applying the latest techniques to solve unique and challenging problems. Requirements: Proven experience developing and deploying machine learning models in a production environment. Strong programming skills in Python & familiarity with ML frameworks (PyTorch or TensorFlow). Solid understanding of ML fundamentals and modern deep learning More ❯

to lead personalization efforts within their CRM ecosystem. You’ll develop predictive models and recommendation systems that enhance customer engagement across global markets. THE ROLE Lead development of machine learning solutions for CRM personalization. Build and optimize recommendation engines using neural networks and deep learnings, incorporating product embeddings and other advanced features to improve relevance and performance. Collaborate … monitoring. Partner with engineering and data teams to ensure scalable solutions. Continuously monitor and improve model performance using data insights and feedback. REQURIED SKILLS & EXPERIENCE Proven experience in machine learning, particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML More ❯