Senior MLOps / LLMOps Engineer Job at ImmoScout24 GmbH (Berlin)

Senior LLMOps Engineer

Working closely with our Engineering Manager, you’ll be a Senior LLMOps Engineer...

Location

Australia , Sydney

Salary:

Not provided

Heidi

Expiration Date

Until further notice

Requirements

Proven track record of designing, building, and maintaining MLOps or LLMOps infrastructure in a production environment
Previous hands-on experience building scalable, cloud-native infrastructure and platforms
Deployed and managed large-scale machine learning models in a production environment
Expert in Python, cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and Infrastructure as Code (e.g., Terraform, CloudFormation)
Deep and practical understanding of the entire machine learning lifecycle and the specific operational challenges of large language models
Ability to translate complex engineering and research requirements into concrete, robust, and automated platform solutions
Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Job Responsibility

Lead the architecture, design, and implementation of our end-to-end LLMOps platform, from data ingestion and model training pipelines to production deployment and monitoring
Build and maintain robust CI/CD/CT (Continuous Integration/Continuous Delivery/Continuous Training) pipelines to automate the testing, validation, and deployment of large language models
Engineer highly available and scalable model serving solutions using modern infrastructure like Kubernetes, ensuring low latency and high throughput for our production services
Collaborate closely with AI research and engineering teams to understand their needs, streamline workflows, and create the tooling that accelerates their development cycles
Champion and implement best practices for model versioning, experiment tracking, monitoring, and governance across the organization
Mentor mid-level and junior engineers, sharing your deep expertise in infrastructure, automation, and operational excellence to foster a culture of reliability and scalability

What we offer

Flexible hybrid working environment, with 3 days in the office
Additional paid day off for your birthday and wellness days
Special corporate rates at Anytime Fitness in Melbourne, Sydney tbc
A generous personal development budget of $500 per annum
Learn from some of the best engineers and creatives, joining a diverse team
Become an owner, with shares (equity) in the company

Fulltime

Senior MLOps Engineer

Prolific is not just another player in the AI space – we are the architects of t...

Location

United Kingdom

Salary:

Not provided

Prolific

Expiration Date

Until further notice

Requirements

5+ years experience with cloud infrastructure and infrastructure as code
Previous experience with the ML and LLM lifecycle - training, hosting, optimisation, observability
Used to working closely with researchers and data scientists - taking experiments from worksheets into production
Strong grasp of ML fundamentals and modern GenAI stack

Job Responsibility

Infrastructure & Platform Engineering: Design and maintain scalable cloud environments (GCP/AWS) using Terraform
Manage GPU/TPU resource allocation for training, fine-tuning, and interactive notebooks
Build internal services and CLI tools to streamline the developer experience for the AI team
ML & LLM Orchestration: Design CI/CD/CT (Continuous Training) pipelines using tools such as GitHub Actions, MLFlow, Vertex AI Pipelines
Develop reusable patterns for model serving
Managing service deployments to Kubernetes
Manage and optimize vector databases and embedding pipelines for RAG-based systems
Performance & Optimization: Implement techniques to reduce latency and increase throughput
Solve scaling bottlenecks for serverless or containerized model deployments
Optimize GPU utilization and cloud spend without compromising performance

What we offer

competitive salary
benefits
remote working
impactful, mission-driven culture

Senior Engineer, Machine Learning Engineering

Mastercard’s Business & Market Insights (B&MI) group empowers organizations to a...

Location

India , Pune

Salary:

Not provided

Mastercard

Expiration Date

Until further notice

Requirements

Master’s/bachelor’s degree in computer science or engineering
Considerable work experience with a proven track-record of successfully leading and managing complex projects/products and delivering to aggressive market needs
Expert-level hands on experience designing, building and deploying both conventional AI/ML solutions and LLM/Agentic solutions
Strong analytical and problem-solving abilities, with quick adaptation to new technologies, methodologies, and systems
Strong applied knowledge and hands on experience in advanced statistical techniques, predictive modelling, machine learning algorithms, GenAI and deep learning frameworks
Experience with AI and machine learning platforms such as TensorFlow, PyTorch, or similar
Strong programming skills in languages such as Python/SQL is a must
Experience with data visualization tools (e.g., Tableau, Power BI) and understanding of cloud computing services (AWS, Azure, GCP) related to data processing and storage is a plus

Job Responsibility

Implement multi-agent intelligence frameworks (LangGraph, CrewAI, AutoGen) to enable reasoning, coordination, and adaptive decision-making across specialized AI agents
Design and operationalize multi-modal AI pipelines combining text, image, tabular, and graph data using transformer-based architectures (BERT, CLIP, LLaVA, T5, Whisper, etc.) for unified intelligence
Build scalable RAG and Graph-RAG systems integrating vector stores and knowledge graphs (Neo4j, AWS Neptune) to enable contextual retrieval, semantic linking, and entity-aware reasoning
Develop and productionize transformer-based models for NLP, vision-language understanding, and sequential prediction tasks leveraging Hugging Face, PyTorch, and TensorFlow ecosystems
Implement advanced Python-based backend services for inference orchestration, async job handling, and distributed data workflows supporting high-throughput AI operations
Establish end-to-end LLMOps and MLOps pipelines on Databricks (AWS) integrating MLflow, feature stores, model lineage, prompt evaluation, and continuous retraining frameworks
Apply traditional AI/ML and statistical modeling techniques (regression, clustering, forecasting, ensemble methods) alongside deep learning models for hybrid interpretability and explainability
Engineer state and memory management subsystems that preserve context, track embeddings, and enable agents to reason temporally across multiple modalities and interactions
Implement Responsible AI practices—bias detection, explainability dashboards, data ethics checks, and performance governance ensuring fairness and transparency of deployed models
Continuously research, benchmark, and productionize innovations in multimodal transformers, generative modeling, and agentic orchestration to drive enterprise-scale intelligence and automation

Fulltime

Senior Ai Engineer

We are currently partnering with multiple clients, ranging from innovative techn...

Location

United Kingdom

Salary:

350.00 - 600.00 GBP / Day

Myn

Expiration Date

Until further notice

Requirements

Professional experience in building and deploying production-grade AI/ML systems
Strong proficiency in Python and modern software engineering practices
Hands-on experience with Large Language Models (LLMs) and Generative AI
Expertise in designing and implementing RAG pipelines and agentic workflows
Proven experience with cloud platforms (AWS, GCP, or Azure) and containerisation technologies like Docker and Kubernetes
A strong understanding of MLOps/LLMOps, including model evaluation, monitoring, and observability
Experience working with vector databases and complex data processing pipelines
The ability to collaborate effectively within cross-functional teams and a product-focused mindset

Job Responsibility

Own the end-to-end lifecycle of AI-powered features, utilising advanced frameworks such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic workflows
Translate high-level requirements into scalable, reliable technical architectures, working closely with product managers, data scientists, and software engineers to ensure seamless integration into existing product ecosystems
Champion robust MLOps and LLMOps practices, implementing rigorous monitoring, evaluation frameworks, and CI/CD pipelines to ensure your solutions remain performant, secure, and maintainable

Senior GenAI Engineer

We are currently seeking a Senior GenAI Engineers to join our team in Bangalore,...

Location

India , Bangalore

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

12+ years IT experience
4+ years in AI/ML/GenAI architecture
Strong data science, MLOps, and solutioning background
Deep expertise with Azure (priority), GCP, AWS
Proven client-facing skills: RFPs, proposals, and stakeholder management

Job Responsibility

Architect and deliver GenAI, LLM, and agentic AI solutions
Excellent understanding of Agentic Frameworks, MLOps, LLMOps
Design enterprise-level scalable AI-ready architectures
Lead proposals, estimations, and RFP/RFI responses
Partner with clients as a trusted AI advisor for transformation roadmaps
Exposure to data engineering pipelines
Build reference architectures and reusable GenAI frameworks

Senior AI Engineer

Location

Australia , South Bank

Salary:

Not provided

Flight Centre Brand

Expiration Date

Until further notice

Requirements

Tertiary qualifications in Computer Science, Software Engineering, Data Science or a related field or equivalent practical experience
Proven experience deploying and operating production-grade agentic AI systems, LLM-powered applications, or ML pipelines with commercial impact
Strong Python programming skills and deep knowledge of modern AI/ML frameworks (e.g. LangGraph, LlamaIndex, PyTorch, scikitlearn)
Solid understanding of classical machine learning, including supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), and time-series forecasting, with hands-on experience taking models to production
Strong experience with Azure cloud services (Azure ML, Azure DevOps, Azure Container Services, Azure Function Apps) and Databricks

Job Responsibility

Lead the design, development, and productionisation of agentic AI workflows, LLM-powered applications, and multi-agent systems
Productionise classical ML models (e.g. classification, regression, time-series forecasting), ensuring they meet production-grade standards for reliability, monitoring, and retraining
Own and evolve end-to-end MLOps and LLMOps pipelines including CI/CD, model registry, drift detection, retraining, and automated evaluation
Build and maintain scalable ML infrastructure on Azure and Databricks including feature engineering pipelines and data platform integrations
Architect and build AI agent workflows, endpoints, gateways, and orchestration layers enabling secure tool usage, structured reasoning, and multi-agent collaboration
Deploy and optimise AI workloads on Kubernetes and cloud-native Azure environments
Define and enforce engineering quality standards through code reviews, design reviews, and technical documentation

What we offer

Individualised Learning & Development pathway options
Access to 'LinkedIn Learning' for ongoing skills development: over 24,500 courses in over 20 languages
Exclusive Staff Discounts: Accessible via our employee-only portal with 350+ of Australia’s leading retailers, health and wellness discounts, financial planning advice, employee share plan and more
Travel Discounts: Including family and friends - flights, hotels, tours, cruises, travel insurance and more
Brightness of Future: Career opportunities in a network of brands and businesses across the globe - we promote from within
Corporate Health Discounts: Access exclusive discounts on health insurance plans for you and your family with our partner, BUPA, access to internal gym
Mental Health: Support and Employee Assistance Program for staff and family
Social: Regular awards nights, social team-building and industry events, with the opportunity to attend global conferences (Bangkok in 2026)
Giving Back: Corporate Social Responsibility program supporting nominated charities through Workplace Giving, volunteering and fundraising
paid parental and volunteer leave

Fulltime

Senior AI Engineer

The Senior AI Engineer at NTT DATA will be responsible for designing and deployi...

Location

South Africa , Johannesburg

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Postgraduate level qualification (Honours or Masters) in Computer Science, Data Science, Engineering, Mathematics, Statistics, Economics or a related field
Alternatively, equivalent practical experience delivering AI or machine learning solutions in enterprise environments
Strong proficiency in Python for AI and machine learning development
Solid understanding of machine learning fundamentals and evaluation techniques
Hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow
Experience working with Generative AI and LLMs in practical use cases
Strong data handling skills, including SQL and data querying
Experience deploying models or AI services into production environments
Experience with vector databases and embeddings (e.g., for RAG architectures)
Experience with cloud platforms (Azure preferred

Job Responsibility

Design and develop Generative AI solutions, including LLM-based applications
Implement techniques such as prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning
Develop and evaluate machine learning models across supervised, unsupervised, and NLP use cases
Optimise model performance, reliability, and cost efficiency for enterprise environments
Work with structured and unstructured data sources (databases, APIs, documents, transcripts, logs)
Collaborate with data engineers to support data ingestion, preparation, and transformation pipelines
Ensure AI solutions are scalable, maintainable, and aligned with software engineering best practices
Package and deploy AI and GenAI solutions into production (APIs, services, batch workflows)
Support cloud-based deployments, primarily on Microsoft Azure, including Azure OpenAI and Azure AI services
Apply MLOps and LLMOps practices such as versioning, monitoring, evaluation, and continuous improvement

Fulltime

Senior AI Engineer

Omio is building the future of travel. We’re moving from manual, rule-based syst...

Location

Singapore , Singapore

Salary:

Not provided

FoodLabs & Atlantic Labs

Expiration Date

Until further notice

Requirements

Minimum 6+ years of experience in developing complex models and algorithms
Proven track record in designing and deploying production-grade AI solutions
Strong communication and presentation skills, with the ability to influence non-technical stakeholders
Self-motivated, independent contributor capable of driving initiatives with minimal guidance
Prior experience deploying scalable AI and LLM-based solutions for real-time, high-performance systems is highly desirable
Expertise in building AI applications using large language models such as OpenAI, Claude, Gemini, LLaMA
Experience with LLM orchestration frameworks like LangChain, LangGraph, vLLM, LMDeploy
Strong programming skills in Java, Python, and SQL
Familiarity with data preprocessing, feature engineering, model evaluation, MLOps, and LLMOps best practices
Ability to construct Retrieval-Augmented Generation (RAG) systems for advanced AI workflows

Job Responsibility

Develop AI solutions leveraging LLMs to improve productivity and deliver strong business impact
Lead the end-to-end development lifecycle from ideation to deployment of AI-powered solutions across various domains
Build scalable AI systems that support Omio’s global expansion goals
Act as an evangelist for AI adoption by demonstrating clear value to stakeholders
Collaborate with Business, Product, and Engineering teams to integrate AI into workflows and drive adoption
Present models, results, and systems to both technical and non-technical audiences, including C-level stakeholders

Fulltime

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Senior MLOps / LLMOps Engineer

Job Responsibility

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