Sr Worldwide Specialist Solutions Architect - GenAI, AmazonSageMaker Job ID: 2858333 | AWS EMEA SARL (UK Branch) Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on … Amazon Web Service (AWS)? Come join us! At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are … by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our more »
Sr Worldwide Specialist Solutions Architect - GenAI, AmazonSageMaker Job ID: 2858333 | AWS EMEA SARL (UK Branch) Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on … Amazon Web Service (AWS)? Come join us! At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are … by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our more »
Sr Worldwide Specialist Solutions Architect - GenAI, AmazonSageMaker DESCRIPTION Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on Amazon Web Service (AWS)? Come join … us! At Amazon, we've been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com's recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes … by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it's a big part of our more »
new relational (SQL) data stores is a key requirement. Experience using AWS cloud technologies and ecosystem including: S3, Lambda functions, AWS Textract, CodeCommit, Cloud9, SageMaker, etc. Proven experience in a range of AI and data science fields: data wrangling, data visualisation, natural language processing, computer vision, deep learning, and more »
and managing production APIs. Software Engineering Best-Practices: Knowledge of industry standards and practices. Preferred Qualifications AWS AI Services: Hands-on experience with AWS SageMaker and/or AWS Bedrock. Data Processing: Experience with high-volume, unstructured data processing. ML Applications: Familiarity with NLP, Computer Vision, and traditional ML more »
Data manipulation Data analysis Pandas Experience with large datasets: Clustering, classification Regression machine learning or deep learning Data presentation AWS knowledge: Lambda functions and Sagemaker Exposure to time series data generated by IoT platforms #J-18808-Ljbffr more »
TensorFlow. Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models, experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2, hands-on experience of building ML solutions on AWS. Strong communication skills, with attention to detail and ability to more »
support business decisions. Support timely delivery of prioritized modelling projects on AIG's modelling platforms - for coded models the platform of choice is AWS Sagemaker AI where our Actuaries create, train, and deploy predictive models used to calibrate raters. Train and support Actuaries in their use of advanced modelling more »
proven experience with big data technologies, specifically Spark and Kafka. You have experience working with state-of-art ML pipeline technologies (such as MLflow, Sagemaker ) or building a ML pipeline by yourself (Docker, Kubernetes, Paperspace, Airflow ). You have a Ph.D. in a quantitative field (computer science, mathematics, physics more »
principles and experience implementing workflows using tools like GitHub Actions or similar. Experience with containerized workflows (e.g., Docker); familiarity with AWS services such as SageMaker, S3, or Lambda is a plus. Experience with model monitoring to ensure deployed models remain accurate and reliable. Familiarity with version control (Git) and more »
or distributed computing frameworks . Proficiency in SQL and NoSQL databases for accessing and preprocessing large datasets. Familiarity with cloud ML services (e.g., AWS SageMaker, GCP AI Platform, Azure ML). Experience deploying ML models in production environments using tools like Docker, Kubernetes , and CI/CD pipelines . more »
agents, and frameworks like vLLM, to drive product innovation. Utilize strong Python skills and work with tools like GitHub, Docker, SQL, PyTorch, and AWS Sagemaker to develop scalable solutions. Participate in a dynamic, fast-paced environment that offers opportunities for professional growth and product ownership. Work closely with a more »
and ML capabilities in production at scale. Strong experience with Python programming and common ML frameworks (e.g., PyTorch, Pandas, NumPy) and MLOps platforms (e.g., SageMaker). Exceptional verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences. Demonstrated ability to work effectively on more »
anomaly detection as well as classical ML models to solve a multifaceted problem. Engineer new features, train and deploy models to production using AWS SageMaker as the MLOps platform. Adopt a data-driven approach to identify gaps in our detection algorithms and propose improvements to our models and algorithms. more »
and ML capabilities in production at scale. Strong experience with Python programming and common ML frameworks (e.g., PyTorch, Pandas, NumPy) and MLOps platforms (e.g., SageMaker). Exceptional verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences. Demonstrated ability to work effectively on more »
Python, with experience in ML libraries such as TensorFlow, PyTorch and Scikit-learn. Experience working with ML training/inference platforms such as Databricks, SageMaker and Seldon. Experience building CI/CD processes with tools such as Jenkins or GitHub Actions. Exemplary communication skills, especially in dealing with multiple more »
the ability to iterate and enhance production models efficiently. Bonus Skills: Familiarity with software development best practices and CI/CD workflows. Experience with AmazonSageMaker for model development and deployment. Get in touch with Joely Callaghan directly at Synchro to find out more! Location: London - Hybrid working more »
the ability to iterate and enhance production models efficiently. Bonus Skills: Familiarity with software development best practices and CI/CD workflows. Experience with AmazonSageMaker for model development and deployment. Get in touch with Joely Callaghan directly at Synchro to find out more! Location: London – Hybrid working more »
business problems Good written and verbal communication skills Preferred Requirements Experience with Machine Learning and Python (time-series analysis, forecasting) Familiarity with AWS environment (SageMaker, S3, Redshift) Familiarity with Snowflake Bachelor's degree in mathematics, statistics, or relevant experience in related field The Perks We trust you, so we more »
visibility. Tech Stack You'll Be Working With Languages : Python, SQL (Postgres) ML/AI Libraries : TensorFlow, PyTorch, scikit-learn, Pandas Infrastructure : Docker, AWS Sagemaker, EKS, EMR, Lambda, Athena Orchestration & Data Tools : Dagster (or Airflow), ClickHouse, Spark We pride ourselves on being technologically adaptable. While the above is our … skills. Experience with tooling for model deployment, monitoring, and performance analysis. Nice-to-Haves: Domain knowledge in retail or e-commerce. Familiarity with AWS (Sagemaker, EKS, EMR, Lambda, Athena). Experience with MLFlow or similar model management tools. Familiarity with Dagster or similar orchestration tools (e.g., Airflow). What more »
Background in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Economics or equivalent) 3+ years of professional working experience Proficiency in Python, AmazonSageMaker, SQL, Jupyter Notebook Experience with Machine Learning and statistical inference Understanding of ETL processes and data pipelines Ability to communicate outcomes of more »
who thrives in developing innovative, state-of-the-art products that can meet and surpass the latest advances in the field Proficiency in Python, AmazonSageMaker, SQL, Jupyter Notebook Experience with Machine Learning and statistical inference. Understanding of ETL processes and data pipelines and ability to work closely more »
who thrives in developing innovative, state-of-the-art products that can meet and surpass the latest advances in the field Proficiency in Python, AmazonSageMaker, SQL, Jupyter Notebook Experience with Machine Learning and statistical inference. Understanding of ETL processes and data pipelines and ability to work closely more »
and validation Model deployment and maintenance Candidate Requirements: Proficiency in Python and SQL for data analysis and machine learning. Strong experience with AWS/SageMaker or other machine learning platforms. Proven ability to work in agile, fast-paced environments with minimal supervision. Some experience in manufacturing OR stock and more »
experience with Python development Established application development experience in Service Oriented Architectures Experience implementing Transformers (ideally, HuggingFace) Fine-tuned Transformer Models (ideally with AWS sagemaker but not essential) Experience deploying models and hosting via an API (AWS is preferred) Experience writing AWS Lambda functions Nice-to-Have Requirements Experience more »
