1 to 25 of 100 MLOps Jobs

and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling and insurance are a plus. Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc are desirable We’ll help you gain Experience working in more »

Physics, Machine Learning Deep expertise in Python (production-level) and SQL Proficiency in machine learning libraries (eg. Pandas, scikit-learn, TensorFlow) and experience with MLOps frameworks for model deployment Exceptional communication skills, able to engage confidently with non-technical stakeholders Experience resolving operational or customer experience-related problems such as more »

About Builder.ai We’re on a mission to make app building so easy everyone can do it – regardless of their background, tech knowledge or budget. We’ve already helped thousands of entrepreneurs, small businesses and global brands, like NBC Universal more »

learning: supervised & unsupervised · Instruct external annotators and manage annotation tasks · Written and verbal communication skills · Presentation skills Desirable skills · SQL · Cloud: AWS · Programming languages · MLOps processes and tools · Interest in the dairy industry is useful · Team leadership or mentoring experience What we’ll offer you in return Full-time, Permanent more »

computational resources, inference speed, and memory efficiency. Good grasp of architecture and how best to integrate machine learning into backend services. Some experience with MLOps processes and tools. Experience with AWS SageMaker would be ideal. Understanding of CI/CD & DevOps principles. Experience working with cloud environments. If you feel more »

health data science/Epidemiology Experience in natural language processing and AI Expertise building statistical models, use of machine learning using Python libraries, and MLOps tools Experience mining and analysing electronic health records (EHR) and knowledge of clinical terminologies i.e. SNOMED-CT Experience with one or more data management tools more »

for people that are comfortable with terms like; Statistical Models, Computer Vision, Predictive Analytics, Data Visualization, Large Language Models (LLM), NLP, AI, Machine Learning, MLOPs, Python, Pyspark, and Azure. Flexible Working : The role is 60% work from home Sponsorship : Sadly sponsorship isn't available for these roles. About You: Bachelors more »

cloud SDKs and APIs. Deep understanding of AI/ML to enhance pipeline efficiency, with experience in TensorFlow, PyTorch, AutoML, Python/R, and MLOps platforms like MLflow and Kubeflow. Solid background in DevOps , including CI/CD automation with Bitbucket Pipelines, Azure DevOps, and GitHub. Capability to automate the more »

functional teams and departments. Willingness to learn new technologies and adapt to evolving industry trends. Desirable Knowledge of Azure ecosystem Experience in working with MLOps frameworks (preferably Azure-ML) Experience with CI/CD pipelines, Test-Driven Development and pipeline automation. more »

MLOps. Responsibilities Design and implement both Data Pipelines for both structured and unstructured data. Support and improve ML infrastructure – particularly Azure ML. Contribute to MLOps across the organisation. Requirements An academic background in Statistics, Mathematics, or Computer Science (or similar) A number of years of commercial work as a Senior more »

MLOps. Responsibilities Design and implement both Data Pipelines for both structured and unstructured data. Support and improve ML infrastructure – particularly Azure ML. Contribute to MLOps across the organisation. Requirements An academic background in Statistics, Mathematics, or Computer Science (or similar) A number of years of commercial work as a Senior more »

handling unstructured data sets Familiarity with software engineering principles and collaborative programming best practices, including version control, testing, and deployment Knowledgeable in DevOps/MLOps methodologies and practices, with experience in cloud environments like Google Cloud Platform or Microsoft Azure Deep passion for data and analytics Proven track record in more »

frameworks (Dask, Modin) Hands on experience with Natural Language Processing (NLP) and Large Language Models (LLMs) Experience of creating and deploying microservices Knowledge of MLOps concepts (CI/CD, versioning, reproducibility, observability) and development best practices ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice more »

and libraries. Experience with ML experiment tracking and collaboration tools like MLflow and Weights & Biases . A strong foundation in software engineering, DevOps practices, MLOps deployment, and infrastructure management. An affinity for generative AI frameworks and SDKs , such as RAG, Langchain, Semantic Kernel, and tools like MS tooling, Co-Pilot more »

environments, ensuring seamless integration with legacy systems. S trong AI and ML principles , with a track record of model development, deployment, and mastery of MLOps practices. Experienced in crafting enterprise-scale cloud-native AI/ML solutions Proficiency in data pipeline orchestration across hybrid environments, leveraging the latest in Azure more »

Scientist in the Financial Services with experience in..... Statistical Models, Computer Vision, Predictive Analytics, Data Visualization, Large Language Models (LLM), NLP, AI, Machine Learning, MLOPs Python, Pyspark, Azure, Agile, MetaBase, then please apply. You can 📧 your cv to matt@hawksworthuk.com or message me on LinkedIn. Ideally you'll have plenty more »

datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB. Understanding of CI/CD pipelines, containerization (Docker, Kubernetes), and experience implementing MLOps practices using Azure DevOps. Strong analytical and problem-solving abilities, with the capability to work on complex issues and drive innovative solutions. Deep understanding of more »

and machine learning, or hold a PhD or Masters degree in a related field such as Computer Science, Maths, Physics, or Engineering Experienced in MLOps, experienced delivering features end-to-end, from architecture design and building through to releasing, testing, and supporting Confident in working in a fast paced environment more »

Build and maintain efficient, scalable, and reliable AI infrastructure, tools, and pipelines to support the deployment of machine learning models in collaboration with the MLOps team. Continuously research and stay current with the latest advancements in AI, machine learning, and data science. Contribute to the growth of the AI team more »

knowledge of machine learning algorithms applied to solving business problems. Proficiency in Python and popular Data Science frameworks (e.g. pytorch, pandas, numpy etc) and MLOps platforms (e.g. Sagemaker) Solid understanding of metrics, benchmarking and evaluation methodology AI-powered user-facing products. Experience working in highly collaborative environments with complex technical more »

techniques as well as evaluating metrics to drive optimizations using tools like Elastic stack, Prometheus, Alibi detect, etc. A solid background in DevOps and MLOps practices, and familiarity with tools to manage infrastructure as code, like Terraform and package managers like Helm Charts. Proficiency with pipeline orchestration tools, such as more »

Introduction Axtria is a global provider of cloud software and data analytics to the Life Sciences industry. We help Life Sciences companies transform the product commercialization journey to drive sales growth and improve healthcare outcomes for patients. We are acutely more »

commercial setting too! Essentials: 5+ years experience as a Data Scientist Proven expertise with deep learning , NLP , and LLMs Expert ability with ML/MLOps Experience mentoring/up-skilling more junior team members. Strengths in SQL , Python ( Pandas , Scikit - Learn , PyTorch ) PhD -level education and experience within Marketing is more »

Principal AI Engineer – GenAI MLOps and GenAI – Hybrid working As a Principal AI/ML Engineer, are you ready to pioneer the future of GenAI technology? You'll have the opportunity to work on the forefront of GenAI technology, strategizing, building, driving innovation and shaping the future of automation solutions. more »

Pandas etc. Commercial experience leveraging open-source models, finetuning LLMs & RAG pipelines Expertise in learning algorithms, neural networks and ML frameworks (TensorFlow, PyTorch etc.) MLOps experience Nice to have: Familiarity with Git or other Version Control Systems Computer Vision Library exposure Understanding of Big Data Technologies (Hadoop, Spark etc) Experience more »