26 to 50 of 77 Remote Apache Airflow Jobs

fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A More ❯

Transformers , PyTorch , YOLO , OpenCV , and Pillow Designing and deploying AI services via FastAPI , AWS Lambda , EKS/ECS , and S3 Creating scalable data pipelines with Pandas , NumPy , SQLAlchemy , and Airflow Supporting real-time model inference, edge deployments, and API integrations Working closely with a technical lead in a service-based and serverless architecture Essential Python Engineer skills and experience More ❯

ideally within consumer tech, logistics, or e-commerce. Strong proficiency in Python, SQL, and machine learning frameworks. Experience with cloud platforms (Azure, AWS, GCP) and tools like Databricks, DBT, Airflow, or Terraform. Familiarity with AI/ML applications and modern analytics tooling. Excellent communication skills and ability to work independently in a fast-paced environment. Why Join? Be part More ❯

As a Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication More ❯

As a Senior Data Engineer you will take ownership of the data platform, optimising it for scalability to ensure successful client onboarding. You'll use modern tools (such as Airflow, Prefect, Dagster or AWS Step Functions) for ETL design and orchestration, work on transformation logic to clean, validate and enrich data (including handling missing values, standardising formats and duplication More ❯

architecture. GraphQL (Working) - queries, mutations, schema awareness. SQL (PostgreSQL) (Working) - schema design, queries, migrations. JavaScript (Working) - legacy code and Jest tests. Go (Awareness) - infrastructure tooling and services. Python (Awareness) - Airflow DAGs and automation scripts. Infrastructure & Cloud AWS (EKS, S3, IAM) Kubernetes fundamentals (pods, services, ingress, Istio, Traefik). Containerization with Docker/containerd.Observability Collaboration Tools Jira, Confluence, Slack, Figma. More ❯

e.g., Erwin, Lucidchart). Strong grasp of data governance, metadata management, and compliance frameworks (e.g., GDPR). Hands-on understanding of Python, SQL, and modern data engineering tools (e.g., Airflow, DBT, Atlan). Exceptional consulting and stakeholder management skills. Career experience within leading consultancies or SIs (e.g., IBM, Thoughtworks, EY, Capgemini). What's on Offer More ❯

C2S). Familiar with Amazon Web Managed Services (AWS). Working knowledge with software platforms and services, such as, Docker, Kubernetes, JMS/SQS, SNS, Kafka, AWS Lambda, NiFi, Airflow, or similar. Proficient experience utilizing JavaScript, Elasticsearch, JSON, SQL, XML. Working knowledge with datastores MongoDB/DynamoDB, PostgreSQL, S3, Redshift, JDBC/ODBC, and Redis. Familiar with Linux/ More ❯

development efficiency and deployment effectiveness, including Azure DevOps or GitHub Considerable experience designing and building operationally efficient pipelines, utilising core Cloud components, such as Azure Data Factory, Big Query, AirFlow, Google Cloud Composer and Pyspark etc Proven experience in modelling data through a medallion-based architecture, with curated dimensional models in the gold layer built for analytical use Strong More ❯

Data Engineer who enjoys coaching & mentoring others, and knowledge sharing. You’ll bring: Strong industry experience within Data Engineering & Cloud Experience with these tools, or familiar: Python, SQL, Kafka, Airflow, Azure, AWS DevOps experience would be a plus (desirable) Formal OR informal Training or Coaching experience (Coach/Mentor/Trainer/Instructor/Tutor/Lecturer etc.) Resilience More ❯

best practices in testing, data governance, and observability. Lead roadmap planning and explore emerging technologies (e.g. GenAI). Ensure operational stability and support incident resolution. Tech Stack Python , SQL , Airflow , AWS , Fivetran , Snowflake , Looker , Docker (You don't need to tick every box - if you've worked with comparable tools, that's great too.) What We're Looking For More ❯

pipelines in Python that run smoothly and efficiently. You understand how to analyze data, spot trends, and communicate your findings clearly. Bonus points if you have worked with DBT, Airflow, Terraform, or have an interest in machine learning and advanced analytics. Above all, you want to grow your technical skills while building things that get used right away. Wat More ❯

contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous work in cybersecurity, anomaly detection, or behavioural analytics. Familiarity with orchestration frameworks (Airflow or similar). Experience with scalable ML systems, pipelines, or real-time data processing. Advanced degree or equivalent experience in ML/AI research or applied science. Cloud platform More ❯

Scala, or in a language such as Java or Python that supports a quick transition to Scala Working with big data technologies, ideally Spark, but experience with tools like Airflow or Elasticsearch is also valuable Manipulating and transforming data - cleansing, parsing, standardising - to improve data quality and integrity Why join Quantexa? Our perks and quirks. What makes you Q More ❯

on development/engineering background Machine Learning or Data background Technical Experience: PySpark, Python, SQL, Jupiter Cloud: AWS, Azure (Cloud Environment) - Moving towards Azure Nice to Have: Astro/Airflow, Notebook Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people More ❯

systems. Deploy scalable AI systems using AWS (Lambda, S3, SQS, EKS/ECS), CDK , and modern DevOps practices. Collaborate on infrastructure and data pipelines using SQLAlchemy, Boto3, Pandas, and Airflow . Contribute to real-time AI services , model versioning, and advanced fine-tuning (LoRA, QLoRA, etc.). AI Engineer requirements: Solid Python skills (3.9+) with deep knowledge of async More ❯

passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have (not essential): Familiarity with dashboarding tools, Typescript, and API development Exposure to Airflow, DBT, Databricks Experience with ERP (e.g. SAP, Oracle) and CRM systems What's On Offer: Salary: £50,000-£75,000 + share options Hybrid working: 2-3 days per More ❯

passion for new technologies Experience in startups or top-tier consultancies is a plus Nice to Have (not essential): Familiarity with dashboarding tools, Typescript, and API development Exposure to Airflow, DBT, Databricks Experience with ERP (e.g. SAP, Oracle) and CRM systems What's On Offer: Salary: £50,000-£75,000 + share options Hybrid working: 2-3 days per More ❯

and AI , or other deep learning-related independent project work with evidence of completion. Experience with data ingestion or processing tools and frameworks, such as Docling, Spark, Pandas, Feast, Airflow, NumPy . Experience with retrieval augmented generation approaches, including vector databases and dense retrieval methods. Knowledgeable in various synthetic data generation approaches, such as GANs, VAEs, or rule-based More ❯

Engineer for our client within defence/digital transformation. The ideal candidate will be able to solve data engineering problems independently whilst delaing with non-technical SMEs. Requirements: Python, Airflow, Glue & Informatica. SC cleared Details: 6 months Outside IR35 Hybrid/London ASAP start date If this role is of interest, please get in touch. Reference: AMC/DJA More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯

network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, DVC, Airflow). Strong problem-solving skills and ability to work independently in a fast-paced environment. Preferred Qualifications: MSc or PhD in Computer Science, Machine Learning, or related field. Experience More ❯