Familiarity with AWS and its tools Excellent communication skills and a collaborative mindset Nice to have: Experience with AI/ML infrastructure or supporting data science workflows Exposure to MLOps tooling or machine learning model deployment More ❯
Familiarity with AWS and its tools Excellent communication skills and a collaborative mindset Nice to have: Experience with AI/ML infrastructure or supporting data science workflows Exposure to MLOps tooling or machine learning model deployment More ❯
Familiarity with AWS and its tools Excellent communication skills and a collaborative mindset Nice to have: Experience with AI/ML infrastructure or supporting data science workflows Exposure to MLOps tooling or machine learning model deployment More ❯
Northampton, Northamptonshire, UK Hybrid / WFH Options
Signify Technology
Familiarity with AWS and its tools Excellent communication skills and a collaborative mindset Nice to have: Experience with AI/ML infrastructure or supporting data science workflows Exposure to MLOps tooling or machine learning model deployment More ❯
data. Collaborate with legal SMEs to translate domain knowledge into scalable machine learning solutions. Continuously evaluate model performance, ensuring accuracy, fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or More ❯
data. Collaborate with legal SMEs to translate domain knowledge into scalable machine learning solutions. Continuously evaluate model performance, ensuring accuracy, fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or More ❯
data. Collaborate with legal SMEs to translate domain knowledge into scalable machine learning solutions. Continuously evaluate model performance, ensuring accuracy, fairness, and compliance. Help shape the data pipeline and MLOps practices for handling sensitive legal content securely. Required Experience: Solid experience with Python and ML/NLP libraries (e.g., spaCy, Hugging Face, TensorFlow/PyTorch). Experience building NLP or More ❯
independently in a hybrid or remote environment. Experience working in agile environments and iterating based on user feedback. Preferred Skills: Background in deploying AI/ML models to production (MLOps). Experience using cloud platforms such as Azure. Interest or experience in building autonomous agents or internal AI assistants. Why Join? Competitive salary, pension and attractive benefits package. Work on More ❯
independently in a hybrid or remote environment. Experience working in agile environments and iterating based on user feedback. Preferred Skills: Background in deploying AI/ML models to production (MLOps). Experience using cloud platforms such as Azure. Interest or experience in building autonomous agents or internal AI assistants. Why Join? Competitive salary, pension and attractive benefits package. Work on More ❯
independently in a hybrid or remote environment. Experience working in agile environments and iterating based on user feedback. Preferred Skills: Background in deploying AI/ML models to production (MLOps). Experience using cloud platforms such as Azure. Interest or experience in building autonomous agents or internal AI assistants. Why Join? Competitive salary, pension and attractive benefits package. Work on More ❯
inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-Agent Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle More ❯
inference using vLLM, DeepSpeed, TensorRT, Triton, and other acceleration frameworks. Multi-Agent Systems : Develop and integrate agentic capabilities using frameworks such as LangChain, CrewAI, AutoGen, and DSPy. AWS Cloud & MLOps: Deploy scalable machine learning workloads on AWS using services like SageMaker, Bedrock, Lambda, S3, DynamoDB, ECS, and EKS. End-to-End AI Product Development : Work across the full ML lifecycle More ❯
