Data Engineer / Ml Engineer — Ai Labs
1 day ago
Burjassot
INSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and experience in scientific research, development, manufacturing, sales, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health. The activities of INSUD PHARMA are organized into three synergistic business areas: Industrial (Chemo), Branded (Exeltis), and Biotech (mAbxience), with over 9,000 professionals in more than 50 countries, 20 state-of-the-art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. INSUD PHARMA believes in innovation and sustainable development. Ready to be a #Challenger? What are we looking for? We're AI Labs — the applied AI team at Insud Pharma. 30 people. AI Engineers, Data Scientists, DevOps Engineers, Product Managers building the systems that power how trials get designed, how patients get recruited, and how everything gets monitored once the trial is live. Clinical trials run on data. Bad pipelines, slow models, and infrastructure that breaks under pressure can cost months — or worse, the trial itself. We are seeking a highly skilled Data Engineer / Machine Learning Engineer to join our Applied AI Team. The ideal candidate combines strong software engineering foundations with hands‑on experience in data pipelines and machine learning systems, and enjoys working at the intersection between data, models, and production systems. As a Data Engineer / MLE at AI Labs, you will work closely with data scientists, software engineers, and product owners to design, build, deploy, and operate end‑to‑end data and machine learning solutions across multiple business units — including Regulatory, Clinical Trials, R&D, Pharmacovigilance, and Drug Manufacturing. This role is critical to ensuring that AI models move reliably from experimentation to production, supported by scalable data pipelines, robust ML infrastructure, and strong engineering standards. How the team works: AI Labs operates with a startup mindset within Insud Pharma. The department is young, and the culture reflects that: flat, collaborative, and fast-moving . You will work alongside Data Scientists, AI Engineers, DevOps Engineers, and Product Managers who are equally committed to delivering high-quality work. We hold regular demo days where teams present their work, as well as whiteboard sessions where we tackle problems together. The cross‑disciplinary dynamic is genuinely strong. The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city. The challenge! Design, build, and maintain scalable data pipelines for data ingestion, transformation, and serving, supporting both analytics and machine learning use cases. Develop and productionize machine learning pipelines , covering training, validation, deployment, and monitoring. Collaborate closely with Data Scientists to translate notebooks and prototypes into robust, production‑ready ML systems . Implement model deployment patterns (batch, real‑time, or hybrid) using APIs, scheduled jobs, or event‑driven architectures. Build and maintain feature pipelines and data abstractions that enable reproducible and reliable model behavior. Ensure data quality, versioning, and traceability across datasets and models. Optimize pipelines and ML workloads for performance, scalability, and cost efficiency. Work with DevOps and Platform teams to deploy solutions using containerization and CI/CD best practices. Contribute to defining data engineering and MLOps standards across AI Labs. Participate in code reviews, documentation, and mentoring to foster a culture of engineering excellence. What do you need? Proficient in Spanish and English , written and verbal communication. Strong proficiency in Python , including clean code practices, packaging, and modular design. Solid understanding of software engineering principles (OOP, SOLID, testing, version control). Hands‑on experience building data pipelines (ETL / ELT) using Python‑based frameworks or custom solutions. Experience working with machine learning workflows , including model training, evaluation, and deployment. Familiarity with REST APIs and service‑based architectures (FastAPI, Flask, or similar). Strong experience with Git and collaborative development workflows. Experience with containerization (Docker) and cloud environments (AWS or Azure). Experience with MLOps practices (model versioning, monitoring, drift detection, retraining strategies). Familiarity with orchestration tools (e.G., Airflow, Prefect, Dagster). Experience with data storage systems (SQL / NoSQL databases, data lakes, object storage). Exposure to streaming or event‑driven architectures. Experience deploying or operating ML systems in regulated or high‑reliability environments. Familiarity with ML frameworks and scientific libraries (NumPy, Pandas, Scikit‑learn, PyTorch, TensorFlow). Interest in applied AI topics such as NLP, LLM‑based systems, or scientific computing. Flexible start time from Monday to Friday Permanent contract. Training and language learning platform ️ Wellness platform with unlimited free psychologist sessions Cabify transportation service for employee use Development plans, internal mobility policy. What will the Selection process be like? ️️ Stay tuned to your phone and email! The first thing we will likely do is contact you through one of the two channels. ️ Prepare well! We will continue with an in‑person/virtual interview depending on availability and what we agree upon; there may be one or twointerviews in the process, and depending on the type of process, there may also be some kind of test. ️ Wait for the result! We care that you feel guided throughout each selection process and know what to expect from us, so we will always try to inform you of the status of the process. Do you think this offer is not for you? Follow us on social media like LinkedIn/Instagram and stay tuned for any offers we may release; the opportunity to be anew Insuder is waiting! COMMITMENT TO EQUAL OPPORTUNITIES The InsudPharma group is aware that business management must align with the needs and demands of society, and therefore assumes the commitment to equal opportunities and treatment between men and women, as stated in the current regulations on the matter - Organic Law 3/2007, and we do not discriminate against any person on the grounds of ethnicity, religion, age, sex, nationality, marital status, affective or sexual orientation, gender identity or expression, disability, or any other personal or social circumstance. INSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and experience in scientific research, development, manufacturing, sales, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health. The activities of INSUD PHARMA are organized into three synergistic business areas: Industrial (Chemo), Branded (Exeltis), and Biotech (mAbxience), with over 9,000 professionals in more than 50 countries, 20 state‑of‑the‑art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. INSUD PHARMA believes in innovation and sustainable development. Ready to be a #Challenger? What are we looking for? We're AI Labs — the applied AI team at Insud Pharma. 30 people. AI Engineers, Data Scientists, DevOps Engineers, Product Managers building the systems that power how trials get designed, how patients get recruited, and how everything gets monitored once the trial is live. Clinical trials run on data. Bad pipelines, slow models, and infrastructure that breaks under pressure can cost months — or worse, the trial itself. We are seeking a highly skilled Data Engineer / Machine Learning Engineer to join our Applied AI Team. The ideal candidate combines strong software engineering foundations with hands‑on experience in data pipelines and machine learning systems, and enjoys working at the intersection between data, models, and production systems. As a Data Engineer / MLE at AI Labs, you will work closely with data scientists, software engineers, and product owners to design, build, deploy, and operate end‑to‑end data and machine learning solutions across multiple business units — including Regulatory, Clinical Trials, R&D, Pharmacovigilance, and Drug Manufacturing. This role is critical to ensuring that AI models move reliably from experimentation to production, supported by scalable data pipelines, robust ML infrastructure, and strong engineering standards. How the team works: AI Labs operates with a startup mindset within Insud Pharma. The department is young, and the culture reflects that: flat, collaborative, and fast‑moving . You will work alongside Data Scientists, AI Engineers, DevOps Engineers, and Product Managers who are equally committed to delivering high‑quality work. We hold regular demo days where teams present their work, as well as whiteboard sessions where we tackle problems together. The cross‑disciplinary dynamic is genuinely strong. The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city. The challenge! Design, build, and maintain scalable data pipelines for data ingestion, transformation, and serving, supporting both analytics and machine learning use cases. Develop and productionize machine learning pipelines , covering training, validation, deployment, and monitoring. Collaborate closely with Data Scientists to translate notebooks and prototypes into robust, production‑ready ML systems . Implement model deployment patterns (batch, real‑time, or hybrid) using APIs, scheduled jobs, or event‑driven architectures. Build and maintain feature pipelines and data abstractions that enable reproducible and reliable model behavior. Ensure data quality, versioning, and traceability across datasets and models. Optimize pipelines and ML workloads for performance, scalability, and cost efficiency. Work with DevOps and Platform teams to deploy solutions using containerization and CI/CD best practices. Contribute to defining data engineering and MLOps standards across AI Labs. Participate in code reviews, documentation, and mentoring to foster a culture of engineering excellence. What do you need? Proficient in Spanish and English , written and verbal communication. Strong proficiency in Python , including clean code practices, packaging, and modular design. Solid understanding of software engineering principles (OOP, SOLID, testing, version control). Hands‑on experience building data pipelines (ETL / ELT) using Python‑based frameworks or custom solutions. Experience working with machine learning workflows , including model training, evaluation, and deployment. Familiarity with REST APIs and service‑based architectures (FastAPI, Flask, or similar). Strong experience with Git and collaborative development workflows. Experience with containerization (Docker) and cloud environments (AWS or Azure). Experience with MLOps practices (model versioning, monitoring, drift detection, retraining strategies). Familiarity with orchestration tools (e.G., Airflow, Prefect, Dagster). Experience with data storage systems (SQL / NoSQL databases, data lakes, object storage). Exposure to streaming or event‑driven architectures. Experience deploying or operating ML systems in regulated or high‑reliability environments. Familiarity with ML frameworks and scientific libraries (NumPy, Pandas, Scikit‑learn, PyTorch, TensorFlow). Interest in applied AI topics such as NLP, LLM‑based systems, or scientific computing. Flexible start time from Monday to Friday Permanent contract. Training and language learning platform ️ Wellness platform with unlimited free psychologist sessions Cabify transportation service for employee use Development plans, internal mobility policy. What will the Selection process be like? ️️ Stay tuned to your phone and email! The first thing we will likely do is contact you through one of the two channels. ️ Prepare well! We will continue with an in‑person/virtual interview depending on availability and what we agree upon; there may be one or twointerviews in the process, and depending on the type of process, there may also be some kind of test. ️ Wait for the result! We care that you feel guided throughout each selection process and know what to expect from us, so we will always try to inform you of the status of the process. Do you think this offer is not for you? Follow us on social media like LinkedIn/Instagram and stay tuned for any offers we may release; the opportunity to be anew Insuder is waiting! COMMITMENT TO EQUAL OPPORTUNITIES The InsudPharma group is aware that business management must align with the needs and demands of society, and therefore assumes the commitment to equal opportunities and treatment between men and women, as stated in the current regulations on the matter - Organic Law 3/2007, and we do not discriminate against any person on the grounds of ethnicity, religion, age, sex, nationality, marital status, affective or sexual orientation, gender identity or expression, disability, or any other personal or social circumstance. INSUD PHARMA operates across the entire pharmaceutical value chain, providing specialized knowledge and experience in scientific research, development, manufacturing, sales, and marketing of a wide range of active pharmaceutical ingredients (API), finished dosage forms (FDF), and branded pharmaceutical products, adding value to human and animal health. The activities of INSUD PHARMA are organized into three synergistic business areas: Industrial (Chemo), Branded (Exeltis), and Biotech (mAbxience), with over 9,000 professionals in more than 50 countries, 20 state‑of‑the‑art facilities, 15 specialized R&D centers, 12 commercial offices, and more than 35 pharmaceutical subsidiaries, serving 1,150 customers in 96 countries worldwide. INSUD PHARMA believes in innovation and sustainable development. Ready to be a #Challenger? What are we looking for? We're AI Labs — the applied AI team at Insud Pharma. 30 people. AI Engineers, Data Scientists, DevOps Engineers, Product Managers building the systems that power how trials get designed, how patients get recruited, and how everything gets monitored once the trial is live. Clinical trials run on data. Bad pipelines, slow models, and infrastructure that breaks under pressure can cost months — or worse, the trial itself. We are seeking a highly skilled Data Engineer / Machine Learning Engineer to join our Applied AI Team. The ideal candidate combines strong software engineering foundations with hands‑on experience in data pipelines and machine learning systems, and enjoys working at the intersection between data, models, and production systems. As a Data Engineer / MLE at AI Labs, you will work closely with data scientists, software engineers, and product owners to design, build, deploy, and operate end‑to‑end data and machine learning solutions across multiple business units — including Regulatory, Clinical Trials, R&D, Pharmacovigilance, and Drug Manufacturing. This role is critical to ensuring that AI models move reliably from experimentation to production, supported by scalable data pipelines, robust ML infrastructure, and strong engineering standards. How the team works: AI Labs operates with a startup mindset within Insud Pharma. The department is young, and the culture reflects that: flat, collaborative, and fast‑moving . You will work alongside Data Scientists, AI Engineers, DevOps Engineers, and Product Managers who are equally committed to delivering high‑quality work. We hold regular demo days where teams present their work, as well as whiteboard sessions where we tackle problems together. The cross‑disciplinary dynamic is genuinely strong. The office is located in central Madrid (Chamberí, near Eloy Gonzalo), well connected and situated in a vibrant part of the city. The challenge! Design, build, and maintain scalable data pipelines for data ingestion, transformation, and serving, supporting both analytics and machine learning use cases. Develop and productionize machine learning pipelines , covering training, validation, deployment, and monitoring. Collaborate closely with Data Scientists to translate notebooks and prototypes into robust, production‑ready ML systems . Implement model deployment patterns (batch, real‑time, or hybrid) using APIs, scheduled jobs, or event‑driven architectures. Build and maintain feature pipelines and data abstractions that enable reproducible and reliable model behavior. Ensure data quality, versioning, and traceability across datasets and models. Optimize pipelines and ML workloads for performance, scalability, and cost efficiency. Work with DevOps and Platform teams to deploy solutions using containerization and CI/CD best practices. Contribute to defining data engineering and MLOps standards across AI Labs. Participate in code reviews, documentation, and mentoring to foster a culture of engineering excellence. What do you need? Proficient in Spanish and English , written and verbal communication. Strong proficiency in Python , including clean code practices, packaging, and modular design. Solid understanding of software engineering principles (OOP, SOLID, testing, version control). Hands‑on experience building data pipelines (ETL / ELT) using Python‑based frameworks or custom solutions. Experience working with machine learning workflows , including model training, evaluation, and deployment. Familiarity with REST APIs and service‑based architectures (FastAPI, Flask, or similar). Strong experience with Git and collaborative development workflows. Experience with containerization (Docker) and cloud environments (AWS or Azure). Experience with MLOps practices (model versioning, monitoring, drift detection, retraining strategies). Familiarity with orchestration tools (e.G., Airflow, Prefect, Dagster). Experience with data storage systems (SQL / NoSQL databases, data lakes, object storage). Exposure to streaming or event‑driven architectures. Experience deploying or operating ML systems in regulated or high‑reliability environments. Familiarity with ML frameworks and scientific libraries (NumPy, Pandas, Scikit‑learn, PyTorch, TensorFlow). Interest in applied AI topics such as NLP, LLM‑based systems, or scientific computing. Flexible start time from Monday to Friday Permanent contract. Training and language learning platform ️ Wellness platform with unlimited free psychologist sessions Cabify transportation service for employee use Development plans, internal mobility policy. What will the Selection process be like? ️️ Stay tuned to your phone and email! The first thing we will likely do is contact you through one of the two channels. ️ Prepare well! We will continue with an in‑person/virtual interview depending on availability and what we agree upon; there may be one or twointerviews in the process, and depending on the type of process, there may also be some kind of test. ️ Wait for the result! We care that you feel guided throughout each selection process and know what to expect from us, so we will always try to inform you of the status of the process. Do you think this offer is not for you? Follow us on social media like LinkedIn/Instagram and stay tuned for any offers we may release; the opportunity to be anew Insuder is waiting! COMMITMENT TO EQUAL OPPORTUNITIES The InsudPharma group is aware that business management must align with the needs and demands of society, and therefore assumes the commitment to equal opportunities and treatment between men and women, as stated in the current regulations on the matter - Organic Law 3/2007, and we do not discriminate against any person on the grounds of ethnicity, religion, age, sex, nationality, marital status, affective or sexual orientation, gender identity or expression, disability, or any other personal or social circumstance. Data Scientist / Machine Learning Engineer BigQuery Dataflow / Dataproc #wearehiring #bluetabanibmcompany #bluetaber #boostyourtalent Git. Scikit-learn. PyTorch / TensorFlow. MLflow. Databricks. PySpark. MLOps. LLMs. RAG. Embeddings. Vector Databases. LangChain / LangGraph. AI Agents. Git. Scikit-learn. PyTorch / TensorFlow. MLflow. Databricks. PySpark. MLOps. RAG. LangChain / LangGraph. #J-18808-Ljbffr
Waiters
Sales & Marketing
Chef & Cook
Retail
Construction & Trades
Accounting & Finance
Animal Care
Art, Media, Design
Cleaning
Customer Service
Driver & Delivery
Education
Engineering
Events & Promotion
Fashion
Host & Hostess
Kitchen Porter
Office & Admin
Sports & Wellness
Warehouse
Writing & Editing
