1,151 to 1,175 of 3,996 Google-Cloud-Platform Jobs

Container Orchestration : Proven track record with Kubernetes/OpenShift in production environments Big Data Ecosystem : Strong background in Hadoop, Hive, Spark, and cloud platforms (AWS/Azure/GCP) Systems Architecture : Understanding of distributed systems, high availability, and fault-tolerant design Security Protocols : Experience with LDAP, Active Directory, OAuth2, and Kerberos authentication Unix/Linux Proficiency : Advanced command-line More ❯

LangChain, Semantic Kernel, Devin). Solid understanding of automation principles and system decomposition. Ability to work independently across varied platforms and repositories. Experience with cloud platforms (Azure, AWS, GCP) and DevOps tools (Terraform, Docker, GitHub Actions). Exposure to AI-integrated developer environments like Cursor or Devin. Scripting experience in Python, TypeScript, or PowerShell. Soft Skills Autonomous and proactive More ❯

presentation skills Hands-on experience in technical integrations and POCs Comfortable coding in any high-level programming language (Java, Go, Python) Strong hands-on knowledge of Kubernetes, AWS, Azure, GCP, Docker, Prometheus, and OpenTelemetry Industry knowledge and opinions on Monitoring, Observability, Log Management, SIEM Engineering/DevOps Background - advantage Experience in Technical Sales of Log Analytics/Monitoring/APM More ❯

industrial sector where data science was applied to core operational or strategic challenges. Proficiency in designing, implementing, and maintaining MLOps processes in a cloud environment (e.g., Azure, AWS, GCP). Technical Skills: Expertise in Python and its ML ecosystem (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Strong background in statistical analysis, algorithm design, and software engineering best practices. More ❯

industrial sector where data science was applied to core operational or strategic challenges. Proficiency in designing, implementing, and maintaining MLOps processes in a cloud environment (e.g., Azure, AWS, GCP). Technical Skills: Expertise in Python and its ML ecosystem (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy). Strong background in statistical analysis, algorithm design, and software engineering best practices. More ❯

applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning More ❯

applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning More ❯

applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning More ❯

applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning More ❯

applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning More ❯

applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in real-world engineering workflows Solid grasp of ML fundamentals: supervised/unsupervised learning More ❯

4+ years’ hands-on backend Java development experience. Strong expertise in RESTful APIs and microservice architectures. Background in distributed systems, OOP, and networking fundamentals. Cloud environment experience (AWS, GCP, etc.), plus Docker/Kubernetes and CI/CD. Proven track record optimising apps for performance, memory, and scalability. SQL/NoSQL database experience, including deployment and integration. Knowledge of More ❯

AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure, AWS or GCP is preferred. Foundational Knowledge: A strong foundation in statistics, mathematics, AI principles and programming is essential for success in this role. Ideally, you will also have Problem-Solving: Ability to More ❯

drift. GenAI/LLMs: RAG, prompt engineering, LoRA fine-tuning, safety, evaluation. Tooling: Python, pandas/PySpark, MLflow, Weights and Biases, Docker, Kubernetes, Terraform, GitHub Actions. Cloud: AWS, GCP, Azure. Soft Skills: problem framing, stakeholder communication, technical writing. What you will bring: 3+ years building and deploying ML systems in production Strong Python and applied ML/DL experience. More ❯

industry experts in consulting and client delivery. Consultants have access to a vast array for different training and certifications in a variety of areas: cloud technologies (AWS, Azure, GCP), programming (Java, Kotlin, NodeJS, Spring Boot), DevOps (Terraform, Kubernetes, Docker), Cybersecurity (CISSP, CISM) and Agile delivery (Scrum Master, Product Owner, Scaled Agile Framework). Capgemini Invent offers you the flexibility More ❯

Overview Who we are Hi, I'm Sheamus, the Senior Tech Lead at Mention Me and I'm hiring! Before I tell you more about the role, here's a little bit about Mention Me and what we do: At More ❯

Machine Learning Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the … provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that’s fusing AI, science, and engineering to push the boundaries of what’s possible. All Machine Learning Engineer positions come with the More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing how the … provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push the boundaries of what's possible. All Machine Learning Engineer positions come with the More ❯

Machine Learning Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the … provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that’s fusing AI, science, and engineering to push the boundaries of what’s possible. All Machine Learning Engineer positions come with the More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's … provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push the boundaries of what's possible. All Machine Learning Engineer positions come with the More ❯

Data Engineer (Palantir) – Senior & Lead London/Remote £70,000 – £120,000 + Bonus – Permanent Currently on the lookout for a Senior Data Engineer to join one of the UK’s leading digital transformation consultancies working at the forefront of More ❯

Job Title: Mid-Senior Java Engineer Location: London (Hybrid - 2-3 days in-office) Salary: Up to £85,000 per annum + Benefits Sector: Financial Services About the Role: We are seeking a Senior-Level Java Engineer to join a More ❯

and learn new languages as a part of internal training and bootcamps. About you Experienced software engineer with strong skills in C#/.NET. Hands-on experience with AWS, GCP or Azure, microservices, and API development. Well-versed in modern software development practices, including unit testing, TDD, CI/CD, SOLID principles, BDD, and agile methodologies. Additional skills (Training provided More ❯

and learn new languages as a part of internal training and bootcamps. About you Experienced software engineer with strong skills in C#/.NET. Hands-on experience with AWS, GCP or Azure, microservices, and API development. Well-versed in modern software development practices, including unit testing, TDD, CI/CD, SOLID principles, BDD, and agile methodologies. Additional skills (Training provided More ❯

and learn new languages as a part of internal training and bootcamps. About you Experienced software engineer with strong skills in C#/.NET. Hands-on experience with AWS, GCP or Azure, microservices, and API development. Well-versed in modern software development practices, including unit testing, TDD, CI/CD, SOLID principles, BDD, and agile methodologies. Additional skills (Training provided More ❯