machine learning engineer in NLP
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Dow Jones is a global provider of news and business information, delivering content to consumers and organizations worldwide across print, digital, mobile, and live event formats. It operates a global newsgathering organization and publishes products including The Wall Street Journal, Barron’s, MarketWatch, Mansion Global, Financial News, Dow Jones Risk & Compliance, and Dow Jones Newswires.
Задачи- Integrate ML models into AI/ML pipelines, including preprocessing, fine-tuning, and deployment
- Implement optimized data storage and indexing systems for NLP
- Develop tools and frameworks for model training, tuning, and evaluation
- Integrate models into production using cloud infrastructure as needed
- Monitor and improve model accuracy and efficiency
- Support ML models, troubleshoot issues, and implement updates
- Build and maintain data processing pipelines for large volumes of structured and unstructured data
- Maintain documentation for ML infrastructure and support processes
- Track developments in GenAI, NLP, ML, and IR, and apply best practices and cloud infrastructure to improve efficiency
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field
- 2–4 Years of industrial experience in machine learning engineering, data science, or data engineering
- 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, such as PyTorch, HuggingFace, LangChain, spaCy, NLTK, or scikit‑learn
- Experience developing and managing NLP‑focused data infrastructure, including storage, indexing, and retrieval systems
- Proficiency in vector storage, indexing, and graph database technologies for scalable cloud operations
- Familiarity with cloud infrastructure and services such as AWS or GCP
- Experience with Docker and Kubernetes on cloud infrastructure
- Experience with Git
- Strong communication and collaboration skills, and a passion for teamwork
- Non-union role
- Competitive and flexible compensation
- The stated pay range is a good‑faith estimate and may vary based on experience, skills, location, and other relevant factors
- Bonus targets for eligible roles are based on market benchmarks and individual contributions
- Eligible roles include a benefits package covering health, retirement, wellbeing, and optional benefits
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