Senior Ml Engineer
- Veracruz, Ver.
- Permanente
- Tiempo completo
Senior ML Engineer
Job Description
The Team
: As a member of the Data Transformation - Cognitive Engineering team you will work on building and deploying ML powered products and capabilities to power natural language understanding, data extraction, information retrieval and data sourcing solutions for S&P Global Market Intelligence and our clients.
You will spearhead deployment of AI products and pipelines while leading-by-example in a highly engaging work environment.
You will work in a (truly) global team and encouraged for thoughtful risk-taking and self-initiative.
What's in it for you:
Be a part of a global company and build solutions at enterprise scale Lead a highly skilled and technically strong team (including leadership) Contribute to solving high complexity, high impact problems Build production ready pipelines from ideation to deployment
Responsibilities:
Design, Develop and Deploy ML powered products and pipelines
Mentor a team of Senior and Junior data scientists / ML Engineers in delivering large scale projects
Play a central role in all stages of the AI product development life cycle, including:
Designing Machine Learning systems and model scaling strategies
Research & Implement ML and Deep learning algorithms for production
Run necessary ML tests and benchmarks for model validation
Fine-tune, retrain and scale existing model deployments
Extend existing ML library's and write packages for reproducing components
Partner with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
Interpret results and present them to business leaders
Manage production pipelines for enterprise scale projects
Perform code reviews & optimization for your projects and team
Lead and mentor by example, including project scrums
Technical Requirements:
Proven track record as a senior / lead ML engineer
Expert proficiency in Python (Numpy, Pandas, Spacy, Sklearn, Pytorch/TF2, HuggingFace etc.)
Excellent exposure to large scale model deployment strategies and tools
Excellent knowledge of ML & Deep Learning domain
Solid exposure to Information Retrieval, Web scraping and Data Extraction at scale
Exposure to the following technologies - R-Shiny/Dash/Streamlit, SQL, Airflow, Redis, Celery, Flask/Django/FastAPI, Scrapy
Experience with SOTA models related to NLP and expertise in text matching techniques, including sentence transformers, word embeddings, and similarity measures
Open to learning new technologies and programming languages as required
A Master's / PhD from a recognized institute in a relevant specialization
Good to have:
5+ years of relevant experience in ML Engineering
Prior substantial experience from the Economics/Financial industry
Prior work to show on Github, Kaggle, StackOverflow etc.
Location: Mexico City (2 days onsite)
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