experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level More ❯
experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What We Offer Culture of Caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level More ❯
in production cloud environments. Advanced Python: Expertise in developing efficient, production-grade AI/ML code. LLMOps & AI Model Management: Experience with tools like MLFlow, LangChain, Hugging Face, Kubeflow, or similar platforms. Data Processing: Proficient with Databricks/Spark for large-scale AI data processing. SQL: Strong capabilities in data More ❯
and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative mindset and ability to work in More ❯
and data modeling. Familiarity with cloud platforms (AWS, Azure, GCP) for deploying ML and data solutions. Knowledge of MLOps practices and tools, such as MLflow or Kubeflow. Strong problem-solving skills, with the ability to troubleshoot both ML models and data systems. A collaborative mindset and ability to work in More ❯
cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work More ❯
cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work More ❯
cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work More ❯
NLP or deep learning techniques (e.g. TF-IDF, word embeddings, CNNs, RNNs). Familiarity with Generative AI and prompt engineering. Experience with Azure Databricks, MLflow, Azure ML services, Docker, Kubernetes. Exposure to Agile development environments and software engineering best practices. Experience working in large or complex organisations or regulated industries. More ❯
teams. Familiarity with LLM (Large Language Model) pipelines and vector databases (e.g. Pinecone, FAISS). Background in data versioning and experiment tracking (e.g DVC, MLflow). Familiarity with time-series datasets and databases. Why Join Quantum? Work at the forefront of AI innovation with a team passionate about changing the More ❯
teams. Familiarity with LLM (Large Language Model) pipelines and vector databases (e.g. Pinecone, FAISS). Background in data versioning and experiment tracking (e.g DVC, MLflow). Familiarity with time-series datasets and databases. Why Join Quantum? Work at the forefront of AI innovation with a team passionate about changing the More ❯
proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯
proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯
proficiency in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯
models Solid grasp of MLOps best practices Confident speaking to technical and non-technical stakeholders 🛠️ Tech you’ll be using: Python, SQL, Spark, R MLflow, vector databases GitHub/GitLab/Azure DevOps Jira, Confluence 🎓 Bonus points for: MSc/PhD in ML or AI Databricks ML Engineer (Professional) certified More ❯
/GCP. · Ability to manage cloud infrastructure to ensure high availability, scalability, and cost efficiency. Nice-to-Have · Experience with ML orchestration platforms like MLflow, SageMaker Pipelines, Kubeflow, or similar. · Familiarity with model quantization, pruning, or other performance optimization techniques. · Exposure to distributed training frameworks like Unsloth, DeepSpeed, Accelerate, or More ❯
/GCP. · Ability to manage cloud infrastructure to ensure high availability, scalability, and cost efficiency. Nice-to-Have · Experience with ML orchestration platforms like MLflow, SageMaker Pipelines, Kubeflow, or similar. · Familiarity with model quantization, pruning, or other performance optimization techniques. · Exposure to distributed training frameworks like Unsloth, DeepSpeed, Accelerate, or More ❯
/ML solutions in production environments Excellent communicator, comfortable working directly with clients and multidisciplinary teams Hands-on experience with MLOps tools such as MLflow, DVC, Kubeflow, Docker/Kubernetes, and GitOps practices Strong working knowledge of Azure and Databricks services Proficient with observability and monitoring tools (e.g. Prometheus, Grafana More ❯
efficient data pipelines to handle text and audio data processing for ML models Deploy NLP models in cloud environments (AWS SageMaker) through Jenkins Use MLflow and other ML Ops applications to streamline ML workflows and adhere to data privacy and residency guidelines Communicate your work throughout the team and related More ❯
teams. Deep knowledge of media measurement techniques, such as media mix modelling. Experience with advanced AI techniques, including NLP, GenAI, and CausalAI. Familiarity with MLFlow, API design (FastAPI), and dashboard building (Dash). If this role looks of interest, reach out to Joseph Gregory More ❯
Git, Linux, and command-line tools. Desirable: Experience with medical image processing, DICOM, ITK/SimpleITK. Familiarity with deploying ML models or MLOps tools (MLFlow, Kubernetes, DVC, Docker). Understanding of the software development lifecycle. Clinical research or commercial experience in regulated/healthcare domains. If you're interested in More ❯
years leading Databricks-based solutions. Proven experience in a consulting environment delivering large-scale data platform projects. Hands-on expertise in Spark, Delta Lake, MLflow, Unity Catalog, and DBSQL. Strong proficiency in Python, SQL, and at least one major cloud platform (AWS, Azure, or GCP). Excellent communication skills and More ❯
years leading Databricks-based solutions. Proven experience in a consulting environment delivering large-scale data platform projects. Hands-on expertise in Spark, Delta Lake, MLflow, Unity Catalog, and DBSQL. Strong proficiency in Python, SQL, and at least one major cloud platform (AWS, Azure, or GCP). Excellent communication skills and More ❯
