Senior Machine Learning Engineer

Posted 3 Days Ago
Be an Early Applicant
Barcelona, Cataluña
In-Office
Senior level
Digital Media • Fintech • Information Technology
The Role
This role involves designing and maintaining machine learning pipelines, integrating models, optimizing infrastructure, and collaborating on AI projects.
Summary Generated by Built In
Job Description:

About the Role

Dow Jones is seeking a skilled Senior Machine Learning Engineer to join our AI Engineering Team, reporting into the ML Engineering Manager. 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). Y

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.

You Will

  • 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.

You Have

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field.
  • +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.
Our Benefits
  • Comprehensive Healthcare Plans for you and your family (paid by Dow Jones)
  • Extra paid Time Off (30 days of holidays/year)
  • Possibility to work remotely for 3 months/year (desplazamiento program) or one week of remote work per quarter
  • Meal benefit with Pluxee (171€/month on top of your salary)
  • Retirement Plans (Dow Jones will pay 2% of a members Pensionable Salary and match employee contribution up to a maximum of 3 %).
  • Comprehensive Insurance Plans
  • Well-being Resources (200 USD allowance per quarter, Classpass, etc.)
  • Family Care Benefits & Caregiving Support
  • Subscription Discounts
  • Employee Referral Program

#LI-Hybrid

This is a hybrid remote/in-office role, based in Barcelona.

Reasonable accommodation: Dow Jones, Making Careers Newsworthy - We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. EEO/Disabled/Vets. We strongly encourage applications from all qualified individuals, including women, people with disabilities, and those from underrepresented groups. Dow Jones is 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, due to a disability, email us at [email protected]. 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.

Business Area:

Dow Jones - Technology

Job Category:

Software Product Engineering

Union Status:

Non-Union role

Top Skills

AWS
Docker
GCP
Git
Huggingface
Kubernetes
Langchain
Nltk
Python
PyTorch
Scikit-Learn
Spacy
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The Company
HQ: New York, NY
4,898 Employees
Year Founded: 1882

What We Do

When you join Dow Jones, you become part of the most dynamic, creative and savvy news and information companies in the world. As a global leader in news and business intelligence, we're newswires, websites, newspapers, apps, newsletters, databases, magazines, and video --including some of the widest-read and most-respected brands, like The Wall Street Journal, Factiva, Barron’s, MarketWatch, Financial News, DJX, Dow Jones Risk & Compliance, Dow Jones Newswires, and Dow Jones VentureSource.

Our products inform the discussions and decisions that are vital to the world's commerce, while our databases make the business world more transparent. We continually develop technology to transform information into insight and prosperity. We enlighten and inspire audiences around the globe with authoritative, differentiated and trusted content.

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