in small cross-functional squads. What we'd like to see from you: Strong understanding of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL More ❯
Preferred Qualifications & Skills: If you have the following characteristics, it would be a plus: Master's or PhD in Computer Science Some experience with MLOps would be very beneficial. Experience with building search applications using Azure Search, Sinequa, Elastic or anything Lucene-based would come in handy but is not More ❯
Experience with big data technologies like Apache Hadoop and Apache Spark. Familiarity with real-time data processing frameworks such as Apache Kafka or Flink. MLOps & Deployment: Experience deploying and maintaining large-scale ML inference pipelines into production environments. Proficiency with Docker for containerization and Kubernetes for orchestration. Familiarity with AWS More ❯
vector databases, and AI inference optimization . Understanding of DevOps practices, CI/CD pipelines, and infrastructure as code (Terraform, Ansible). Familiarity with MLOps and AI model deployment pipelines is a plus. Why Join Us? Work on cutting-edge AI applications with a talented and passionate team. Opportunity to More ❯
data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts for More ❯
data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts for More ❯
data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts for More ❯
party Generative AI API services Setting up Retrieval Augmented Generation (RAG) architectures, prompt engineering (ICL), and Reinforcement Learning from Human Feedback (RLHF) processes Implement MLOps and related DevOps focused on LLMs deployed in cloud-native environments Support, optimise and transition our current processes to ensure well architected implementations and best More ❯
be beneficial include: Experience in a startup environment Knowledge of Python frameworks (Django, Flask, FastAPI), Rust, and machine learning libraries Familiarity with Generative AI, MLOps, CI/CD, and cloud platforms (AWS/GCP/Azure) Expertise with container tools like Docker and Kubernetes Ready to take the next step More ❯
tools and frameworks such as TensorFlow, PyTorch, MLflow, SageMaker, or Databricks Deep understanding of data architecture, APIs, and model deployment best practices Knowledge of MLOps and full model lifecycle management Excellent communication and stakeholder management skills Desirable MSc or PhD in Computer Science, Artificial Intelligence, or a related field Experience More ❯
Experience Databricks Machine Learning Associate or Machine Learning Professional Certification Developed and deployed real-time pricing, recommendation or next best action models Understanding of MLOps We are actively seeking candidates for full-time, remote work within the UK. More ❯
Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL More ❯
south west london, south east england, United Kingdom Hybrid / WFH Options
SR2 | Socially Responsible Recruitment | Certified B Corporation™
our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align More ❯
west london, south east england, United Kingdom Hybrid / WFH Options
SR2 | Socially Responsible Recruitment | Certified B Corporation™
our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align More ❯
SR2 | Socially Responsible Recruitment | Certified B Corporation™
our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align More ❯
london, south east england, United Kingdom Hybrid / WFH Options
SR2 | Socially Responsible Recruitment | Certified B Corporation™
our platform. Ensure smooth end-to-end integration of AI/ML functionality within broader product development efforts. Technical Leadership Define best practices for MLOps, model deployment, and performance tuning. Evaluate and implement new frameworks, tools, and cloud-native AI solutions (including LLMs). Make strategic technical decisions that align More ❯
south west london, south east england, United Kingdom
SoftServe
and technologies. The GenAI Strategy at SoftServe aims to spearhead the development and implementation of intelligent software systems that integrate GenAI, AI, Data Analytics, MLOps, and Cloud infrastructure. IF YOU ARE A holder of a Ph.D. or master's Degree in Computer Science, or a related field Experienced in Generative More ❯
and technologies. The GenAI Strategy at SoftServe aims to spearhead the development and implementation of intelligent software systems that integrate GenAI, AI, Data Analytics, MLOps, and Cloud infrastructure. IF YOU ARE A holder of a Ph.D. or master's Degree in Computer Science, or a related field Experienced in Generative More ❯
frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and cloud platforms (AWS, Azure, GCP) • Strong experience with data architecture, pipelines and governance (e.g., data lakes, ETL, MLOps) • Knowledge of regulatory and ethical considerations in AI systems • Excellent leadership, communication and stakeholder engagement skills Desirable: • TOGAF or other enterprise architecture certification • Experience deploying More ❯
CI/CD for microservices or ML pipelines. Solid understanding of networking, Linux, and security fundamentals. Preferred Qualifications Experience supporting GPU‐accelerated workloads or MLOps/LLMOps platforms. Familiarity with service mesh (Istio, Linkerd) and event‐driven architectures (Kafka, Pub/Sub). Knowledge of distributed storage systems (Ceph, MinIO More ❯
CI/CD for microservices or ML pipelines. Solid understanding of networking, Linux, and security fundamentals. Preferred Qualifications Experience supporting GPU‐accelerated workloads or MLOps/LLMOps platforms. Familiarity with service mesh (Istio, Linkerd) and event‐driven architectures (Kafka, Pub/Sub). Knowledge of distributed storage systems (Ceph, MinIO More ❯
CI/CD for microservices or ML pipelines. Solid understanding of networking, Linux, and security fundamentals. Preferred Qualifications Experience supporting GPU‐accelerated workloads or MLOps/LLMOps platforms. Familiarity with service mesh (Istio, Linkerd) and event‐driven architectures (Kafka, Pub/Sub). Knowledge of distributed storage systems (Ceph, MinIO More ❯
for complex property management workflows and decision-making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings Preferably hands More ❯
