100% Remote, USA Six Feet Up is seeking a Senior Data Engineer with deep experience designing, building, and maintaining secure, scalable data systems. In this role, you will work with cross-functional teams to turn complex data challenges into reliable production solutions. You will design data pipelines, build processing workflows, improve data quality, support machine learning initiatives, and help clients make better use of structured, unstructured, time-series, sensor-based, and high-volume data. We are looking for someone who can bring technical leadership, sound engineering judgment, and strong communication skills to ambiguous data problems. The ideal candidate is comfortable working across data engineering, cloud infrastructure, machine learning support, and production software delivery. As a Senior Data Engineer, you will: Design, build, and maintain robust, scalable data pipelines Develop ETL/ELT workflows for collecting, transforming, validating, and storing data Work with cloud-based data processing and storage systems Implement data validation, quality checks, monitoring, and transformation workflows Process complex datasets, including noisy, high-volume, time-series, sensor, or device-generated data Support machine learning workflows, including data preparation, model training, evaluation, and production integration Collaborate with data scientists, researchers, software engineers, and client stakeholders Translate prototype data workflows into reliable, maintainable production systems Create systems that are well-documented, testable, secure, and ready for audit or review Communicate technical tradeoffs clearly to both technical and non-technical audiences If you are a motivated Senior Data Engineer seeking a challenging and meaningful role, we encourage you to apply. We are looking for someone with strong hands-on experience in: Data pipeline architecture and implementation ETL/ELT orchestration tools such as Airflow, Dagster, or similar platforms Python-based data engineering and data processing tools Cloud-based data infrastructure, storage, and processing Data modeling, schema design, validation, and quality-control practices Working with public, proprietary, structured, and unstructured datasets Time-series, sensor, IoT, or other high-volume data sources Supporting machine learning or data science teams with reliable data workflows Building reproducible, testable, and maintainable data systems Version control, automated testing, and collaborative software development practices Strong candidates may also have experience with: Machine learning pipelines for classification, prediction, recommendation, or categorization systems MLOps, model evaluation, experiment tracking, and reproducible ML workflows Processing noisy signal data or other data that requires cleaning, filtering, or feature extraction Healthcare, digital health, research, or regulated software environments HIPAA, privacy-preserving data architecture, or secure cloud data processing Working with sensitive, clinical, or user-generated data Helping researchers or domain experts scale early-stage algorithms into production-ready systems Designing systems that support thousands or more users A Plus: Experience with containers, CI/CD, DevOps practices, or Kubernetes Familiarity with AWS, Google Cloud, Azure, or similar cloud platforms Experience with consumer analytics, dashboards, or data visualization products Experience supporting FDA, SaMD, clinical validation, audit, or regulatory documentation efforts Experience designing secure data workflows for privacy-sensitive applications About You You are a senior engineer who brings structure to ambiguous technical challenges. You ask thoughtful questions, identify risks early, and know how to balance research needs, business goals, engineering quality, and long-term maintainability. You care about data quality, privacy, testing, documentation, and clear communication. You are comfortable designing architecture, writing production code, reviewing data workflows, and collaborating with people from different technical backgrounds. You enjoy helping clients move from ideas and prototypes to secure, scalable, production-ready systems.

Durham, North Carolina, USA We are looking for Agentic AI Scientists eager to utilize their expertise in these advanced technologies to revolutionize our drug development processes. In the Pharmaceutical Technology and Development (PT&D) department, you will be a key player in transforming molecules into groundbreaking medical treatments. Your role involves contributing data science expertise into cross functional global pharmaceutical development projects in support of transforming the way we deliver medicines to patients. You'll play a pivotal role in shaping our AI strategy and driving the co-development of sophisticated HITL multi-agent systems. We are hiring two candidates for this position and the roles will be based at our dynamic site in Durham (USA). Essential skills/Experience: PhD in computer science, data science, artificial intelligence, machine learning or related fields. At least 3 years of experience in Deep Learning and ML Excellent coding skills in languages such as Python, R. Hands-on industrial experience designing multi-agent patterns, digital twins and experience with agentic AI design patterns, reinforcement learning. Extensive industrial experience with AI and ML frameworks like TensorFlow, PyTorch, Hands-on experience with GenAI orchestration frameworks such as LangGraph, CrewAI Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable Baselines. Hands-on industrial experience with applied machine learning domains such as deep learning, NLP, GenAI. Desirable skills/experience: Contributions to open-source projects. If you meet these criteria, please highlight merged GitHub PRs in your application. Strong publication record in the field of AI. Experience designing multi-agent systems in the pharmaceutical sector. Experience delivering machine learning projects with applications in pharmaceutical development, chemical engineering or chemistry. Experience with one or more of the following applied machine learning domains such as transfer learning, federated learning, few/zero shot learning, meta learning, explainable AI.

Montreal, QC, Canada Role Overview As Data Acquisition & Infrastructure Engineer, you will be the foundation of MAI's data capabilities. Your primary focus will be the development and operation of automated data collection pipelines that aggregate publicly available information from across the art market ecosystem. You will also own the design and maintenance of the underlying database infrastructure — built on PostgreSQL and AWS — that stores and serves this data. This is a high-ownership role. The infrastructure is partially built; you will take it to production scale. You will work closely with AI engineers, a computer vision engineer, a product manager, full-stack developers, and the Head of Art Research, reporting directly to the Head of AI Engineering. Key Responsibilities DATA PIPELINE & COLLECTION Architect and maintain automated pipelines that collect, normalize, and ingest publicly available art market data from web-based sources Build reliable, maintainable collection systems using Python (Scrapy, BeautifulSoup, Playwright, or equivalent), with a strong emphasis on resilience, scheduling, and data freshness Manage pipeline orchestration and scheduling using tools such as Apache Airflow, AWS EventBridge, or cron Navigate the practical challenges of large-scale public data collection, including access patterns, rate constraints, and source reliability Handle messy, inconsistent real-world datasets — clean, transform, and standardize data for downstream consumption DATABASE ENGINEERING Design, build, and maintain relational database schemas in PostgreSQL (hosted on Amazon RDS) to support complex, multi-entity art market data — artists, works, transactions, provenance, and valuation history Develop and optimize queries, indexes, and data models to ensure performance at scale Establish and enforce data quality standards, validation rules, and integrity constraints across the database Collaborate with AI engineers and the computer vision team to ensure the data layer supports model training and inference requirements INFRASTRUCTURE & OPERATIONS Deploy and manage pipeline workloads on AWS (Lambda, EC2, S3, RDS) Monitor pipeline health, data freshness, and system reliability — proactively address failures Contribute to infrastructure-as-code practices as the team scales Core Requirements 3–5 years of professional experience in data engineering or a closely related discipline Proven experience building and maintaining automated data collection pipelines from web-based public sources using Python (Scrapy, BeautifulSoup, Playwright, or Selenium) Strong data cleaning and normalization skills, with demonstrated ability to handle heterogeneous, inconsistent real-world datasets Solid PostgreSQL experience: schema design, query optimization, and database maintenance Hands-on AWS experience: Lambda, EC2, S3, RDS Experience scheduling and orchestrating data pipelines (Apache Airflow, AWS EventBridge, or equivalent) Experience navigating the constraints of large-scale public data collection, including reliability, access patterns, and data freshness challenges Nice to Have Knowledge of data quality frameworks and validation pipeline design Experience with containerization (Docker) and infrastructure-as-code (Terraform, AWS CDK) Familiarity with ETL/ELT tooling (dbt, AWS Glue, or equivalent) Exposure to art market platforms (Christie's, Sotheby's, Artsy, Artnet) or understanding of how auction and gallery data is structured Background or genuine interest in the art world, collectibles, or alternative asset markets Experience in a startup or early-stage environment where ownership and adaptability are essential

Remote, Remote Contract hours: Full time Location: Remote (within 2 hours of London timezone) Salary: €25k - €30k depending on experience About Adzuna Adzuna is a job search engine that lists every job, everywhere. From our launch in the UK in 2011, we now have tens of millions of visitors a month and are busy conquering the world from our HQ in West London alongside our remote teams - helping millions of people find better, more fulfilling jobs. We already have a suite of AI-powered tools (such as ValueMyCV, Prepper and ApplyIQ) built by our talented team and their passion for building new AI-powered tech for job seekers. We're a commercially minded team that moves fast, takes ownership and loves what we do. About the Role This is a fantastic opportunity for a talented Junior Python Developer to join our fast moving AI & Innovation Team. You will play a vital role in building and maintaining our full stack - scaling robust backend services, while developing the user facing web components that power our cutting edge AI products and jobseeking tools. You’ll be working in a tight knit, cross-functional team alongside Product Managers, Data Scientists and Senior Engineers. This is a high growth role where you will learn how to transition machine learning prototypes into robust, production ready applications for millions of users, while simultaneously honing your coding, frontend and architecture skills. What You'll Do Fullstack Development: Write clean, testable, and efficient Python code to support our core AI products and automated search and apply tools. Model Integration: Collaborate closely with our Data Scientists to integrate machine learning models, LLM pipelines and agentic frameworks into our live production stack. API & Data Pipelines: Build and maintain scalable APIs and data workflows to handle large volumes of job vacancy data. Infrastructure & DevOps: Help manage and optimise our AWS infrastructure, ensuring high availability and smooth deployment processes. Testing & Quality: Write robust unit and integration tests to ensure system reliability and mitigate deployment risks. Tech Stack Includes Languages & Frameworks: Python, Spark, LLMs & LLM coding tools Frontend: React, HTML, CSS (Tailwind) AWS Ecosystem: EC2, S3, Lambda, Step Functions, RDS, Athena, Kinesis Databases & Search: PostgreSQL, MySQL, SOLR While we look out for all of these skills, we do not expect experience in all of them. We value a strong foundation in core programming principles and a genuine eagerness to learn. Experience: 1–2 years of commercial software development experience using Python Location: Fully remote (must be located within a 2-hour timezone of London and able to work standard UK business hours). Right to Work: This is a long-term role structured via a contractor agreement for international remote compliance. Candidates must have the legal right to work remotely as an independent contractor in their country of residence. We are unable to provide visa sponsorship for this position now or in the future. Communication: Professional proficiency in English (both written and verbal) to collaborate effectively with a global team. Education: A technical degree (2:1 or equivalent) in Computer Science, Software Engineering, or a highly relevant field. Core Coding Skills: Solid understanding of Python fundamentals and object-oriented programming. Execution: Record of writing clean, maintainable Python code into live, user-facing environments. Databases: Good working knowledge of SQL and relational databases. Cloud & Tools: Familiarity with AWS services and Git version control. Mindset: A curious, proactive fast learner who loves solving technical puzzles and is excited by the AI/ML space. Nice to have Frontend Coding Skills: Familiarity with HTML, CSS (Tailwind) and React to assist in building fullstack user interfaces. AI Applications: Experience with coding LLMs into production applications, and effectively utilising LLM coding tools in your daily workflow. Browser Automation: Understanding of web scraping techniques, DOM parsing, and bypassing common bot-detection. Experience with browser automation and testing tools (e.g. Playwright, Selenium). Portfolio: An active GitHub profile showcasing examples of your work, or personal projects.