Machine Learning Engineer at S&P Global

Gdansk, Pomeranian Voivodeship, Poland

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Not SpecifiedCompensation

Junior (1 to 2 years), Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

AutomotiveIndustries

Requirements

2-3 years of hands-on experience building and deploying machine learning models in a production environment
Experience with ML Ops pipelines
Experience with Gitlab and Gitlab CI on AWS and Kubernetes
Experience with Tensorflow and Sagemaker
5+ years of professional software engineering experience (preferred)
Strong proficiency in Python (preferred)

Responsibilities

Implement a service to provide machine learning models developed by data analysts for new product features
Build and maintain a robust ML Ops pipeline for continual training, quality testing, regression testing, and deployment of machine learning models
Provide expert guidance to data analysts and other team members on machine learning model selection, architecture, and best practices

Skills

Key technologies and capabilities for this role

ML OpsGitLabGitLab CIAWSKubernetesTensorFlowSageMakerPythonMachine LearningModel Deployment

Questions & Answers

Common questions about this position

Is this Machine Learning Engineer position remote?

Yes, this is a fully remote position.

What is the salary for this Machine Learning Engineer role?

This information is not specified in the job description.

What skills are required for the Machine Learning Engineer position?

Required skills include 2-3 years of hands-on experience building and deploying ML models in production, experience with ML Ops pipelines, Gitlab and Gitlab CI on AWS and Kubernetes, and Tensorflow and Sagemaker. Preferred qualifications are 5+ years of professional software engineering experience and strong proficiency in Python.

What is the team culture like for this role?

The team culture emphasizes 'No jerks allowed' and includes regular CARFAX events to help colleagues connect internally. The team consists of over 100 colleagues from over 20 nations across Europe.

What makes a strong candidate for this Machine Learning Engineer role?

A strong candidate will have 2-3 years of hands-on experience building and deploying ML models in production, expertise in ML Ops pipelines, Gitlab CI on AWS and Kubernetes, and Tensorflow/Sagemaker, with preferred experience of 5+ years in software engineering and strong Python skills.

S&P Global

Provides financial information and analytics services

About S&P Global

S&P Global provides financial information and analytics to a wide range of clients, including investors, corporations, and governments. The company offers services such as credit ratings, market intelligence, and indices, which help clients understand and navigate the global financial market. S&P Global's products work by utilizing advanced data analytics and research to deliver insights that assist clients in making informed decisions and managing risks. Unlike many competitors, S&P Global has a diverse range of divisions, including S&P Global Ratings and S&P Dow Jones Indices, which allows it to cater to various financial needs. The company's goal is to support clients in driving growth while also committing to corporate responsibility and positive societal impact.

New York City, New YorkHeadquarters

1917Year Founded

IPOCompany Stage

Data & Analytics, Financial ServicesIndustries

10,001+Employees

Benefits

Health Insurance

Unlimited Paid Time Off

Professional Development Budget

401(k) Company Match

Family Planning Benefits

Employee Discounts

Risks

Integration challenges with new acquisitions like ProntoNLP may cause operational issues.

Increased competition from AI-driven platforms like Brooklyn Investment Group.

Dependence on volatile credit ratings market could impact revenue stability.

Differentiation

S&P Global integrates advanced AI tools for superior financial analytics capabilities.

The company offers comprehensive ESG solutions, meeting growing sustainability demands.

S&P Global's diverse divisions provide a wide range of financial services globally.

Upsides

Acquisition of ProntoNLP boosts data analytics and sentiment scoring capabilities.

Rising demand for ESG data enhances S&P Global's market position.

Expansion into India strengthens S&P Global's research and insights offerings.

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