276 to 300 of 1,401 Algorithms Jobs

or Bachelor with 5+ years of experience architecting ML/AI solutions in diverse domains. Technical Expertise: Proficient in Generative AI, reinforcement learning, multi-agent systems, and decision-making algorithms, with hands-on experience using Python, and modern AI frameworks. Cloud & Tools Proficiency: Skilled in deploying solutions on cloud platforms like AWS, Azure, GCP, Databricks, and Snowflake. Business & Communication Acumen More ❯

or Bachelor with 5+ years of experience architecting ML/AI solutions in diverse domains. Technical Expertise: Proficient in Generative AI, reinforcement learning, multi-agent systems, and decision-making algorithms, with hands-on experience using Python, and modern AI frameworks. Cloud & Tools Proficiency: Skilled in deploying solutions on cloud platforms like AWS, Azure, GCP, Databricks, and Snowflake. Business & Communication Acumen More ❯

be part of reshaping the labour market and becoming the worlds leading job platform. Job Description Join our team and youll be responsible for our recommender systems and search algorithms,building the core infrastructure that powers millions of meaningful connections. Working in theSearch & Match domain, you willbe focusing on deploying and scaling machine learning models, particularly large language models (LLMs More ❯

years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 2 years of experience with data structures or algorithms in either an academic or industry setting. 2 years of experience with Android application development. Experience using Kotlin/Java. Preferred qualifications: Master's degree or PhD in Computer Science More ❯

role. Experience in technology architecture, enterprise architecture. Experience in AI/GenAI product management and technology system life-cycle management. In-depth understanding of AI and machine learning concepts, algorithms and techniques, and AI/GenAI lifecycle. In-depth understanding of technical and system architecture, leading development of conceptual design and working with technical teams around solutioning. Strong knowledge of More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

third-party providers. Familiarity with cloud environments such as Google Cloud or AWS, and deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. Why Synthesis? Synthesis is known for More ❯

third-party providers. Familiarity with cloud environments such as Google Cloud or AWS, and deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. Why Synthesis? Synthesis is known for More ❯

third-party providers. Familiarity with cloud environments such as Google Cloud or AWS, and deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. Why Synthesis? Synthesis is known for More ❯

third-party providers. Familiarity with cloud environments such as Google Cloud or AWS, and deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. Why Synthesis? Synthesis is known for More ❯

third-party providers. Familiarity with cloud environments such as Google Cloud or AWS, and deploying data science workflows at scale Strong grasp of statistical methods and core machine learning algorithms , with practical experience using libraries such as scikit-learn, statsmodels, and the ability to select appropriate models based on data characteristics and problem context. Why Synthesis? Synthesis is known for More ❯

to modeling, simulation, and analysis of mechanistic or data-driven models of biological processes through software development in a highly collaborative environment. This will include: - Exploring and developing ML algorithms to solve complex problems and draw conclusions. Apply state of the art AI tools to infer and model cellular dynamics from large data sets Applying strong coding experience to model More ❯

could be effectively applied to contractual/legal Apply NLP techniques in order to maintain and extend the current rule based, supervised and unsupervised methods Apply ML/DL algorithms and technologies to NLP tasks such as Named Entity Recognition, POS tagging, Parsing, Sentiment Analysis, Clustering, text prediction etc. Develop a comprehension of the technologies, methods and the architecture within More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

even footballers’ legs. Ki’s mission is simple. Digitally disrupt and revolutionise a 335-year-old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days. Ki is proudly the biggest global algorithmic insurance carrier. It is the fastest growing More ❯

Python data science ecosystem. Experience with distributed computing frameworks like Apache Spark (PySpark) or similar is preferred Data Science/ML: Strong experience in exploratory data analysis, machine learning algorithms, statistical inference, and experimental design, with desirable experience in optimisation techniques (e.g., linear/non-linear programming, or heuristics) Ownership: Proven track record of successfully leading and shipping end-to More ❯

in the world - and doing this alongside an experienced team. JOB PURPOSE We are looking for an AI Consultant who not only knows exactly how to create impact with algorithms, big data, machine learning, and generative AI, but can also translate our tech offerings to our current and future clients as well as our wider digital marketing teams internally. As More ❯

in the world - and doing this alongside an experienced team. JOB PURPOSE We are looking for an AI Consultant who not only knows exactly how to create impact with algorithms, big data, machine learning, and generative AI, but can also translate our tech offerings to our current and future clients as well as our wider digital marketing teams internally. As More ❯