Senior Machine Learning Engineer

dowjones; Barcelona; On-site; EUR 90,000 - 120,000; Full time

Job summary

Dow Jones, based in Barcelona, seeks a Senior Machine Learning Engineer to design, build, and maintain ML pipelines and infrastructure for both traditional and GenAI models. You will collaborate with data scientists to integrate diverse models and optimize deployment, monitoring, and scaling across cloud environments.

Requirements include 2–4 years in ML/DS/DE roles, strong Python skills, NLP/ML frameworks experience, and knowledge of cloud, Docker, Kubernetes, and Git.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field.

Responsibilities

• Collaborate with data scientists and engineers to integrate ML models into AI/ML pipelines, covering pre-processing, fine-tuning, and deployment.
• Implement optimized data storage and indexing systems for NLP, utilizing advanced database technologies.
• Develop tools and frameworks for model training, tuning, and evaluation, ensuring seamless infrastructure integration.
• Partner with data scientists and engineers to integrate models into production, leveraging cloud infrastructure as needed.
• Monitor and improve model performance for accuracy and efficiency.
• Provide ongoing support, troubleshoot issues, and implement updates for ML models.
• Build and maintain data processing pipelines for high volumes of structured and unstructured data.
• Develop and maintain documentation for all ML infrastructure and support processes.
• Stay updated on GenAI, NLP, ML, and IR technologies, incorporating best practices and leveraging cloud infrastructure for efficiency

Skills

Python

NLP

PyTorch

HuggingFace

LangChain

spaCy

NLTK

scikit-learn

Cloud computing

Docker

Kubernetes

Git

Data collaboration

Communication

Education

Bachelor's or Master's in CS/Engineering/Data Science

Tools

AWS

GCP

Job description

Job Description:

Position: Senior Machine Learning Engineer

Location: Barcelona

Department: Technology

About the Role

Dow Jones is seeking a skilled Senior Machine Learning Engineer to join our AI Engineering Team. You will be responsible for designing, building, and maintaining machine learning pipelines and infrastructure, supporting both conventional and GenAI models. You will collaborate with our data scientists to seamlessly integrate various machine learning models, including large language models (LLMs).

As a key team member, you will play a crucial role in operationalizing machine learning solutions to meet our organization's needs and deliver tangible value. You will leverage your strong software engineering skills to develop robust, secure, and scalable production systems, utilizing your expertise in machine learning algorithms and techniques.

Responsibilities

• Collaborate with data scientists and engineers to integrate ML models into various AI/ML pipelines, covering pre-processing, fine-tuning, and deployment.

• Implement optimized data storage and indexing systems for NLP, utilizing advanced database technologies.

• Develop tools and frameworks for model training, tuning, and evaluation, ensuring seamless infrastructure integration.

• Partner with data scientists and engineers to integrate models into production, leveraging cloud infrastructure as needed.

• Monitor and improve model performance for accuracy and efficiency.

• Provide ongoing support, troubleshoot issues, and implement updates for ML models.

• Build and maintain data processing pipelines for high volumes of structured and unstructured data.

• Develop and maintain documentation for all ML infrastructure and support processes.

• Stay updated on GenAI, NLP, ML, and IR technologies, incorporating best practices and leveraging cloud infrastructure for efficiency

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field.

• 2-4 years of industrial experience in a machine learning engineering, data science or data engineering role.

• Strong programming skills in Python and/or another high-level language commonly used in machine learning.

• Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.).

• Experience in developing and managing NLP-focused data infrastructure, including storage, indexing, and retrieval systems.

• Proficiency in vector storage, indexing, and graph database technologies for scalable operations in cloud environments.

• Familiarity with cloud-based infrastructure and services (e.g., AWS, GCP, etc.).

• Experience with containerization and orchestration technologies, such as Docker and Kubernetes, on cloud-based infrastructure.

• Experience with version control systems such as Git.

• Strong communication and collaboration skills, and a passion for working as part of a team.

Equal Opportunity Employer

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status or any other protected characteristic. We strongly encourage applications from all qualified individuals, including women, people with disabilities, and those from underrepresented groups.

Reasonable Accommodation

We are committed to providing reasonable accommodation for qualified individuals with disabilities in our job application and/or interview process. If you need assistance or accommodation in completing your application or participating in an interview due to a disability, email us at [e-mail]. Please put "Reasonable Accommodation" in the subject line and provide a brief description of the type of assistance you need. This inbox will not be monitored for application status updates.

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Business Area:

Dow Jones - Technology

Job Category:

Software Product Engineering

Union Status:

Non-Union roleBase Pay Range: -

We’re committed to offering competitive and flexible compensation to attract top talent. This pay range reflects our good faith estimate for the role and may vary based on a candidate’s experience, skills, location, and other relevant factors.

For bonus-eligible roles, targets are determined based on multiple considerations, including market benchmarks and individual contributions.

For benefits-eligible roles, we offer a comprehensive and competitive benefits package covering health, retirement, wellbeing, and more, along with optional benefits to meet the diverse needs of our employees.