2,276 to 2,300 of 2,666 Remote Machine Learning Jobs

impact-focused VCs and supported by partners including UCL, Innovate UK, Microsoft, and Google. The role We're looking for an AI/ML Data Scientist to join our London team. You'll work directly alongside our founders and engineers who've previously built at Meta, Atlassian, and more … wider codebase where it makes sense (Python, Postgres, AWS, some Next.js) What we’re looking for - At least 2 years in a data science, ML, or applied research role, post-graduation - Hands-on experience evaluating or benchmarking AI/ML systems: you've built evals, designed metrics, or run structured ...

expertise in designing and implementing solutions leveraging cloud services (particularly AWS), with a particular emphasis on cloud-native integration patterns and AI/ML services.Proven track record (projects or in a lead role) in an AWS Technical Architect or Lead Engineer capacity, specifically designing and delivering complex cloud-native solutions … incorporating AI/ML components.Strong and specialised experience and understanding of TMT products, processes, and technologies in areas such as:Media industry, covering areas like content platforms, ad tech, and rights management platformsDigital platforms and technologiesAppreciation of emerging technology and trends in TMT with an understanding and knowledge of different ...

Enablement Ubuntu Pro Services - Our key commercial offerings Ubuntu Pro, Compliance, Standards, Security Engineering, and Managed Services on cloud and on prem AI/ML & MLOps - Open source AI/ML solutions, AIOps automation, model lifecycle management, Kubeflow, MLFlow, KServe, and AI infrastructure on cloud and edge IoT - Ubuntu … technologies and the tech landscape A strong work ethic, and personal interests aligned with the open source movement Curiosity, and the habit of continuous learning A strong sense of ownership Problem solving and the ability to innovateOutstanding communications skills in English, both verbal and written For more senior positions ...

Domains and their capabilities within Azure/GCP and SME experience in at least one area. Familiarity in AWS is also desirable. AI/ML security: Knowledge of AI/ML threats and risks, with experience applying security controls for secure deployment of AI services in cloud platforms. Application Security ...

EPAM Systems in London is seeking an AI Consultant to lead AI and ML initiatives for financial services, combining risk, compliance, and analytics expertise. You will design, deploy, and govern AI solutions, collaborating with risk, compliance, and legal teams. The role requires strong Python skills, experience with cloud platforms (Azure ...

based, hybrid work with 3 days in the office, allowing collaboration with data science, data engineering and DevOps teams. You'll build and deploy ML/NLP solutions, explore LLMs, and partner with product and engineering to deliver production-ready models across AWS and Azure, improving compliance and safety outcomes. ...

relax on your schedule Benefits Packages: Competitive medical, dental and vision benefits along with a monthly wellness allowance to keep you healthy and happy Learning & Development Allowance: Your continued growth and development are important to us Dynamic Team: Strong investment in the best talent at the intersection of technology ...

just written: Dagster or Airflow, S3-based data flows, and a habit of testing outputs for correctness rather than only for exceptions. Applied ML in production: embeddings and semantic similarity, clustering, or operationalising models (not necessarily training from scratch). AWS fluency and CI/CD discipline. Nice to have … Practical LLM engineering: prompting, batch inference, and cost and throughput trade-offs across providers. SageMaker, Bedrock, or comparable managed ML tooling. Financial and equities domain knowledge: classification taxonomies, factor models, index construction. Valuable but learnable. Infrastructure as code (AWS CDK or Terraform) and Docker. Experience we're looking ...

agents, recommendation systems, decisioning systems, personalization, or next-best-action experiences.Experience building the backend orchestration, services, APIs, and feedback loops that connect AI or ML models to real customer actions and outcomes.Experience working with complex, high-volume data and ensuring AI outputs are relevant, explainable, trustworthy, and useful to customers.Experience … defining evaluation, monitoring, and learning mechanisms to assess the quality and impact of AI-generated recommendations or insights.Ability to partner effectively with ML and data science teams to integrate and productionize models, without necessarily owning model training or core ML infrastructure.Strong product judgment and customer empathy, with the ability ...

your teams A track record of understanding, assessing, and embracing new tooling and trends within the software industry Built or integrated AI/ML features into products and systems, including recommendation engines, NLP, computer vision, predictive analytics, RAG pipelines, and agents Successfully led modernisation and replatforming efforts to align legacy … deadlines Advising clients on architecture, scalability and platform evolution, connecting technical decisions to product and business outcomes Collaborating on systems that involve the full ML lifecycle from data ingestion and preprocessing, to model deployment, integration, and performance monitoring Driving innovation by proactively surfacing new technical approaches and product solutions Leading ...

recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals. The Role The Principal ML Infrastructure Engineer will extend and operate the infrastructure that powers our research model training, fine-tuning, and serving pipelines. You will be embedded within … Research function, partnering directly with ML engineers and research scientists to ensure they can train Large Physics Models efficiently and reliably at scale. Team Context In this role, you will be vertically embedded in Research, working daily with: Research Scientists who determine the model architectures and methods ML Engineers ...

your skill and experience.Essential RequirementsYou will have a PhD in a relevant discipline and circa 10+ years of demonstrable experience in an AI/ML role in industry or academia, preferably in the Defence sector.You will have experience of previously leading R&D teams.You will have experience of previously undertaking … Engineering Assurance activities.Proposal writing experience is essential.Of particular interest are candidates with experience in one or more of the following domains:AI/ML for imagery including applied to remote sensing applications.Reinforcement learning.Natural Language Processing.Large Language Models.Knowledge graphs and graph-based neural nets.AI/ML for RF and EW, radar ...

join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future … Hybrid: Demonstrated experience in a role that blends product management (defining the "what" and "why") with software engineering (defining the "how"). AI/ML Expertise: Deep subject matter expertise in applying modern AI/ML techniques to solve real-world business problems. Experience with NLP, predictive modeling, or generative ...

join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future … Engineering Hybrid: Demonstrated experience in a role that blends product management (defining the "what" and "why") with software engineering (defining the "how").AI/ML Expertise: Deep subject matter expertise in applying modern AI/ML techniques to solve real-world business problems. Experience with NLP, predictive modeling, or generative ...

join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future … Hybrid: Demonstrated experience in a role that blends product management (defining the “what” and “why”) with software engineering (defining the “how”). AI/ML Expertise: Deep subject matter expertise in applying modern AI/ML techniques to solve real-world business problems. Experience with NLP, predictive modeling, or generative ...

breadth and depth of expertise. We’re at the forefront of change and you’ll have an opportunity play a part in this while learning from the best people in the market!Accountabilities –Challenge the status quo in insurance pricing by developing innovative pricing solutionsOwn … predict claims outcomes, fraud and other risk KPIsSupport the development of junior analysts within the teamSkills Knowledge & Experience -Proficiency in Python, SQL, Azure ML, Git, Azure Cloud Services (Essential)Multiple track record of delivery of ML projects from EDA to deployment, post deployment evaluation and model refreshing. (Essential)Work accurately ...

from discovery through delivery and iteration, incorporating rapid experimentation, prototyping, and AI‐assisted development Identify, shape, and prioritise AI/GenAI/agentic/ML use cases, translating them into scalable product features and measurable business outcomes Partner closely with data science and engineering teams to bring ML models … responsible AI by embedding governance, explainability, and regulatory considerations into product design and lifecycle Mentor and lead multidisciplinary teams, fostering a culture of experimentation, learning, and AI & data fluency What We’re Looking For Experience in developing and delivering digital products/portfolios across B2B, B2C, or B2B2C contexts ...

seeking a Data Scientist to push the boundaries of experience innovation. You will design and deploy fraud and banking analytics, generative AI, and production ML pipelines within an Agile, client-facing environment that values collaboration, learning, and responsible AI practices. The role offers hybrid work options and international opportunities. ...

currency) across domains AI, Analytics & Data Products Define the architecture for data products – curated, well‐documented datasets served to analytics, reporting, and AI/ML consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly … context), Glue, Lake Formation, IAM, VPC Data Governance Data lineage, cataloguing (Apache Atlas/Collibra/Snowflake Horizon), GDPR, BCBS 239, MDM AI/ML Data Query & Performance SQL optimisation, clustering keys, partitioning, query profiling, cost‐based tuning Data Landscape The Data Architect will work across the following technology landscape. ...

pipelines for ingesting CAE/CFD/FEA engineering data, ensuring zero I/O bottlenecks. Integrate traditional physics solvers (OpenFOAM/Simcenter) into ML pipelines for active learning and model refinement. Setup \"physics-aware\" CI/CD and experiment tracking (Kubeflow/MLFlow) that validates physical consistency laws. … Skills/Must have Orchestration: Expert-level Kubernetes (AKS/EKS) is essential. ML Frameworks: Strong proficiency in PyTorch, JAX, or NVIDIA NeMo. HPC/Data: Solid experience with Python, Go, and distributed data tools (Dask/Spark). Background: Experience in AI research labs (e.g., DeepMind, OpenAI) or Neocloud ...

assurance, and identity verification capabilities. You will lead cross-functional teams to deliver innovative computer vision and verification solutions, work closely with engineering and ML teams to advance our AI capabilities, and shape the future of digital content safety, all while ensuring compliance with evolving regulatory requirements including the Online … marketplaces Strong understanding of API-first product development and platform integrations Solid technical background with the ability to work effectively with engineering and ML teams Understanding of modern software architecture, APIs, and cloud-based content processing pipelines Ability to translate complex AI/ML concepts, content safety challenges, and regulatory ...

fleet (VS Code, Python, Git, CLI utilities), balancing developer flexibility with security and compliance standards. Define and support endpoint requirements for AI/ML workloads, including GPU driver management, containerization/WSL2, and local model runtime resource sizing. Partner with engineering and data teams to evaluate, standardize, and roll … Support, Including Configuring and troubleshooting VS Code, Python, and common CLI/developer environments Git‐based version control workflows Endpoint requirements for AI/ML workloads (GPU drivers, WSL2/containers, local model runtimes, resource sizing) Applying governance and device‐management guardrails to developer and AI tooling without blocking productivity ...

across the fleet (VS Code, Python, Git, CLI utilities), balancing developer flexibility with security and compliance standards.Define and support endpoint requirements for AI/ML workloads, including GPU driver management, containerization/WSL2, and local model runtime resource sizing.Partner with engineering and data teams to evaluate, standardize, and roll … workload support, including:Configuring and troubleshooting VS Code, Python, and common CLI/developer environmentsGit-based version control workflowsEndpoint requirements for AI/ML workloads (GPU drivers, WSL2/containers, local model runtimes, resource sizing)Applying governance and device-management guardrails to developer and AI tooling without blocking productivityAbility ...

fleet (VS Code, Python, Git, CLI utilities), balancing developer flexibility with security and compliance standards. Define and support endpoint requirements for AI/ML workloads, including GPU driver management, containerization/WSL2, and local model runtime resource sizing. Partner with engineering and data teams to evaluate, standardize, and roll … support, including: Configuring and troubleshooting VS Code, Python, and common CLI/developer environments Git-based version control workflows Endpoint requirements for AI/ML workloads (GPU drivers, WSL2/containers, local model runtimes, resource sizing) Applying governance and device-management guardrails to developer and AI tooling without blocking productivity ...

environments.Define and operationalise SLOs, SLIs, and error budgets across platform services.Improve capacity planning, scaling strategies, and resource efficiency across large GPU-backed clusters.Partner with ML, platform, and software teams to establish clear production readiness standards.Incident Response & On-CallParticipate in a 24/7 on-call rotation as first-line response … experience.Essential skillsProven experience in an SRE, Production Engineer, or Cloud Reliability role supporting large-scale cloud systems.Experience operating GPU-backed environments or large-scale ML infrastructure.Experience running model training or inference pipelines in production (MLOps).Strong Kubernetes experience, including operating production clusters.Hands-on experience running production workloads ...