Ensuring AI practices comply with policies and ethics Providing technical guidance to cross-functional teams Programming in Python, Java, .NET, JavaScript, or C++ Using MLOps tools and frameworks Source control with Git, Mercurial, or Perforce Containerization with Docker, Kubernetes Additional experience in the following is desirable but not mandatory, and … we will support your development: Refining models in collaboration with data scientists Improving MLOps processes Ensuring data quality and accessibility Performing data analysis for model development Documenting model development processes Working with cloud environments like AWS or Azure Integrating with various database systems Using CI/CD tools such as More ❯
Data Lake House infrastructure to support AI and Data Analytics Research Manage Cloud/On-premises compute resources to achieve research objectives Contribute to MLOps pipeline for translation of Research Algorithms to Product Collaborate with researchers, academic partners, product team, and image analysts Manage cohorts of test data according to … AI model training pipelines and architectures (transformers, diffusion models etc) Understanding of fundamental statistical concepts (p-values, effect sizes and confidence intervals) Experience with MLOps methodologies Experience with version control (e.g. GitLab, DVC) Experience with Data Governance in a regulated industry (GDPR, EU AI Act) Experience translating research to product More ❯
you Drive the evolution of our data platforms by shaping the design, deployment and ongoing support of our tooling/capabilities for data streaming, MLOps, and batch- and real-time analytics Focus on what matters: whether its reducing time to first insight for our internal customers, or proactively reducing the … have any of the following experiences too; Deep familiarity with modelling approaches for cloud data lakehouses/medallion architectures Building, extending or extensively using MLOps frameworks (open-source or otherwise), particularly for applications in support of customer personalisation Surfacing analytical products into data visualisation platforms (we use PowerBI) via semantic More ❯
you Drive the evolution of our data platforms by shaping the design, deployment and ongoing support of our tooling/capabilities for data streaming, MLOps, and batch- and real-time analytics Focus on what matters: whether it's reducing time to first insight for our internal customers, or proactively reducing … have any of the following experiences too; Deep familiarity with modelling approaches for cloud data lakehouses/medallion architectures Building, extending or extensively using MLOps frameworks (open-source or otherwise), particularly for applications in support of customer personalisation Surfacing analytical products into data visualisation platforms (we use PowerBI) via semantic More ❯
Senior MLOps (Full Stack) Engineer London Foundation Models What you'll do Build and maintain APIs (FastAPI or similar) to serve ML models Design and manage robust ML infrastructure using Kubernetes, Docker, and Terraform Deploy machine learning models into production environments Responsibilities Collaborate with ML teams to streamline training, deployment More ❯
Gotobeat – The operating system for live music Location: Remote-first (UTC to UTC+3 preferred) | Type: Full-time, Permanent | Reports to: Head of Tech How to apply: send your CV to alfredo@gotobeat.com About Gotobeat Gotobeat uses AI-driven, event-driven More ❯
HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered on digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all More ❯
london, south east england, United Kingdom Hybrid / WFH Options
Gotobeat
Gotobeat – The operating system for live music Location: Remote-first (UTC to UTC+3 preferred) | Type: Full-time, Permanent | Reports to: Head of Tech How to apply: send your CV to alfredo@gotobeat.com About Gotobeat Gotobeat uses AI-driven, event-driven More ❯
HCLTech is a global technology company, home to 219,000+ people across 54 countries, delivering industry-leading capabilities centered on digital, engineering and cloud, powered by a broad portfolio of technology services and products. We work with clients across all More ❯
Senior Applied Scientist II page is loaded Senior Applied Scientist II Apply remote type Remote Job: Hybrid locations CHE-Zug-Landis+Gyr-Strasse 3 GBR-London-5 Canada Square time type Full time posted on Posted Yesterday job requisition id JREQ190974 More ❯
Career Opportunities: Microsoft AI - Senior Consultant (10532) Requisition ID 10532 - Posted - Years of Experience (2) - Consulting - Where (1) - Job We are a boutique AI consulting and services firm specialising in assembling AI solutions for business impact. Our focus is on More ❯
as a Senior Software Engineer at Monolith AI: As a Senior Software Engineer at Monolith AI, you'll contribute to developing our self-serve MLOps platform that empowers domain experts to harness AI without deep technical expertise. Using your strong Python backend skills, you'll create intuitive tools that enable … non-technical users to build robust MLOps pipelines, focusing on platform maturation, data scale, quality, and automation. Working alongside experienced senior engineers, you'll bring a data engineering mindset to the team, building sophisticated systems that parallel orchestration tools like Airflow or Temporal. Rather than creating individual pipelines, you'll … real bonus, but not a requirement if: You've worked in a start-up environment. You've got DBT experience. You've familiarity with MLOps principles and practices and their application in a production setting. Interview Process: You'll have a 20-minute conversation with one of our internal recruiters More ❯
With over 10 years at the forefront of the MLOps space, Seldon's mission is simple: to enable businesses to take control of complexity, offering real-time machine learning deployment with enhanced observability and flexibility. At Seldon, we're not just about technology. We're about people. As a small … professionally. About the role You will be joining our small but mighty team of talented engineers primarily working on our next-generation data-centric MLOps platform (Seldon Core v2) that allows users to scale to 1000s of models in production and build powerful data-driven ML inference pipelines using Kafka. … involved in the continued development of our suite of LLM and Data Science focused modules. Help design, build and extend Seldon's Core v2 MLOps platform, contributing to improved reliability, scalability and performance as well as next-generation features. Engage in technical discussions about the architecture of the system and More ❯
our labelling, training and production inference data pipelines to produce high quality datasets, models and services to power our automated vehicle inspection product. Following MLOps and DevOps best practices you will build and deploy bespoke computer vision ML models using a service-oriented architecture in AWS, GCP and on Edge … may be reasonably required to fulfil DeGould's objectives. Depending on the individual role, some or all of the following: Developing and championing robust MLOps frameworks and policies. Training and maintaining performant vehicle segmentation models. Labelling tasks and data quality. Designing and implementing reporting dashboards. Developing novel approaches from academic … PyTorch, Keras, or Tensorflow. Working knowledge of core AWS concepts and services such as EC2, ECS, EKS, and DynamoDB. Good knowledge of DevOps and MLOps tools, including usage of Git, Bash, UNIX, Docker, containers and CI/CD pipelines (GitHub Actions or similar). Able to work effectively both as More ❯
consistent model deployment. · Implement and maintain infrastructure-as-code to manage scalable, secure, and elastic cloud-based ML environments. · Ensure seamless orchestration of the MLOps lifecycle, including experiment tracking, model registry, deployment automation, and monitoring. · Manage ML model lifecycle on AWS (preferred) or other cloud platforms. · Understand LLM architecture fundamentals … inference and training. Technical Proficiency: · Programming experience in Python and C/C++, especially for inference optimization. · Solid understanding of the end-to-end MLOps lifecycle and related tools. · Experience with containerization, image building, and deployment (e.g., Docker, Kubernetes optional). Cloud & Infrastructure: · Hands-on experience with AWS services for More ❯
consistent model deployment. · Implement and maintain infrastructure-as-code to manage scalable, secure, and elastic cloud-based ML environments. · Ensure seamless orchestration of the MLOps lifecycle, including experiment tracking, model registry, deployment automation, and monitoring. · Manage ML model lifecycle on AWS (preferred) or other cloud platforms. · Understand LLM architecture fundamentals … inference and training. Technical Proficiency: · Programming experience in Python and C/C++, especially for inference optimization. · Solid understanding of the end-to-end MLOps lifecycle and related tools. · Experience with containerization, image building, and deployment (e.g., Docker, Kubernetes optional). Cloud & Infrastructure: · Hands-on experience with AWS services for More ❯
Hands-on Technical Leadership Serve as a player-coach-writing code, prototyping models, conducting experiments, and reviewing designs. Establish best practices for data science, MLOps, and model deployment at scale. Guide the selection of AI technologies, platforms, and tooling. Team Building & Mentorship Mentor team members and the broader business, fostering … following: LLMs, agent frameworks, RAG, knowledge representation, or autonomous data pipelines. Strong programming and software engineering skills (Python preferred; familiarity with cloud-native and MLOps tools). Demonstrated experience in building and deploying AI systems in production environments. Strong understanding of data governance, bias, fairness, and regulatory considerations in AI. More ❯
RED are currently looking for 2X Data Science Engineer's to work on a project with a client of ours based in London. This position will be a contract position running initially until the end of this year + extensions More ❯
RED are currently looking for 2X Data Science Engineer's to work on a project with a client of ours based in London. This position will be a contract position running initially until the end of this year + extensions More ❯
Come and change the world of AI with the Kumo team! Companies spend millions of dollars to store terabytes of data in data lakehouses, but only leverage a fraction of it for predictive tasks. This is because traditional machine learning More ❯
Introducing Productboard Pulse. Exec-level insights into what your customers need, powered by AI. At Productboard, we fundamentally believe that the world's best products are created by product makers who possess an exceptionally deep understanding of their customers' needs. More ❯
Job ID: Amazon Development Centre (India) Private Limited The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research More ❯
As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team, you will work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering More ❯
channelling our start-up mentality every step of the way - meaning you'll have the opportunity to make a real impact. As a Principal MLOps Engineer at JPMorgan Chase within the International Consumer Bank, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted … the firm's culture of diversity, equity, inclusion, and respect. Required qualifications, capabilities and skills Formal training or certification on software engineering concepts and MLOps applied experience. Experience with machine learning engineering and operations in a large enterprise. Experience in building, evaluating and deploying ML models into production. Experience leading More ❯
