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Lead AI/ML Engineer

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Mastercard

Aug 23, 2024

  • Job
    Full-time
    Senior Level
  • Data
    Software Engineering
  • Dublin
    Remote
  • Quick Apply

AI generated summary

  • You need 5+ years in AI/ML, enterprise model deployment, APIs, Kubernetes, DataOps/MLOps, SQL, Big Data, Python, CI/CD tools, and strong communication skills. Mentor others in a fast-paced environment.
  • You will deploy large-scale AI/ML solutions, design Kubernetes operators, collaborate cross-functionally, manage production systems, and mentor data scientists and ML engineers through code reviews.

Requirements

  • - 5+ years of experience working in AI/ML technology domain or similar
  • - Experience in building and deploying AI/ML models in enterprise production environments/large scale projects with modern light weight design
  • - Experience in APIs and micro-service architectures
  • - Fundamental knowledge and hands-on experience with Kubernetes
  • - Hands-on experience with DataOps and MLOps - namely development, testing, deployment and monitoring of data and ML pipelines; using tools like MLFlow, KubeFlow, AirFlow or similar
  • - Experience with SQL and relational database systems like Oracle, PostgreSQL or MySQL
  • - Experience building large scalable and reliable enterprise technology platforms using Big Data open-source technologies such as Hadoop, Spark and Kafka
  • - Good knowledge and understanding of AI/ML model families, including neural net, decision trees, Bayesian models, deep learning algorithms(LSTM, CNN etc.)
  • - Proficiency with Python programming and machine learning libraries such as NumPy, Pandas, Scikit-learn, Tensorflow and/or PyTorch
  • - Ability to learn new technologies quickly and mentor Data Science team members in AI/ML domain
  • - Experience with Continuous Integration/Continuous Deployment (CI/CD) tools such as Jenkins
  • - Self-starter and self-motivated with the proven ability to deliver results in a fast-paced, high-energy environment
  • - Excellent communication/presentation skills

Responsibilities

  • Responsible for deploying modern and large scale end-to-end AI/ML solutions
  • Design and implementation of Kubernetes operators and micro-services for orchestrating AI/ML workloads
  • Work cross-functionally with data scientists, data engineer, and business stakeholders to design, develop, deploy, and integrate high-performance machine learning pipelines and data intensive workloads
  • Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads
  • Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers

FAQs

What is the main focus of the Lead AI/ML Engineer role at Mastercard?

The main focus of the Lead AI/ML Engineer role is to deploy modern and large-scale end-to-end AI/ML solutions, working closely with data scientists and business stakeholders to design, develop, and integrate high-performance machine learning pipelines.

What are the key responsibilities of a Lead AI/ML Engineer?

Key responsibilities include designing and implementing Kubernetes operators for AI/ML workloads, taking ownership of production systems, and providing technical mentorship to data scientists and ML engineers.

What qualifications are needed for this position?

Candidates should have 5+ years of experience in the AI/ML domain, experience in deploying AI/ML models in enterprise environments, and proficiency in Python programming and machine learning libraries.

Are there any specific technologies or tools that a Lead AI/ML Engineer should be familiar with?

Yes, familiarity with Kubernetes, DataOps and MLOps tools like MLFlow, KubeFlow, and AirFlow, as well as experience with Big Data technologies such as Hadoop, Spark, and Kafka, is important.

Is there an opportunity for professional development in this role?

Yes, the position offers opportunities for technical mentorship and the chance to learn new technologies quickly, as well as to mentor other team members in the AI/ML domain.

What kind of projects would the Lead AI/ML Engineer work on?

The Lead AI/ML Engineer would work on large-scale AI/ML projects, building and deploying models in enterprise production environments, and creating scalable, reliable technology platforms.

How does Mastercard emphasize corporate security responsibility for its employees?

Employees are expected to abide by security policies, ensure the confidentiality and integrity of information, report any suspected security violations, and complete periodic mandatory security trainings.

What skills are important for success in this role?

Important skills include strong communication and presentation abilities, experience with CI/CD tools, and a self-starter attitude to deliver results in a fast-paced environment.

What kind of work environment can the Lead AI/ML Engineer expect at Mastercard?

The work environment is designed to be inclusive and supportive, fostering a culture where individual strengths and experiences are respected, leading to better decision-making and innovation.

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Mastercard

Connecting Everyone to Priceless Possibilities

Consulting
Industry
10,001+
Employees
1966
Founded Year

Mission & Purpose

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.