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Machine Learning Engineer

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Radancy

29d ago

  • Job
    Full-time
    Junior Level
  • Data
    Software Engineering
  • Hamburg

AI generated summary

  • You should have 2+ years in ML, AWS, Docker, Kubernetes, strong Python skills, NLP knowledge, CI/CD experience, and preferably AdTech experience, along with debugging and model optimization skills.
  • You will develop and manage ML infrastructure, optimize models, implement algorithms, assist data scientists, troubleshoot issues, and write efficient code while integrating with databases.

Requirements

  • 2+ years as a Machine Learning Engineer or equivalent experience.
  • Hands-on experience with AWS, docker and Kubernetes.
  • Experience in debugging complex system issues.
  • Strong Python programming skills, particularly for data intensive tasks.
  • Knowledge of machine learning fundamentals and model optimization techniques.
  • Understanding of NLP, language models, and their applications.
  • Prior involvement in projects involving bid optimization or budget allocation.
  • Understanding of CI/CD pipelines (bitbucket pipelines / github workflows), terraform is a plus.
  • Experience working in AdTech is a plus.

Responsibilities

  • Platform and Infrastructure development
  • Manage and improve the machine learning serving platform, leveraging AWS. Work with the DevOps team to ensure scalability, security, and reliability of the infrastructure.
  • Contribute to diverse projects, including bid optimization, budget allocation, natural language processing (NLP), and large language models (LLMs).
  • Project Deployment and Support
  • Implement new algorithms and improve the quality of current production algorithms
  • Assist other data scientists in deploying new machine learning projects.
  • Troubleshoot production issues
  • Model Performance Optimization
  • Hyperparameter optimization across systems of multiple algorithms.
  • Implement long run solutions to mitigate model concept drift over months and years.
  • Development and Analysis
  • Write efficient, maintainable code using the modern python data science stack
  • Integrate with and query databases, particularly PostgreSQL and Delta Lake.

FAQs

What is the main role of the Machine Learning Engineer at Radancy Programmatic?

The main role involves building the infrastructure and algorithms for our production programmatic advertising allocation system and collaborating closely with data scientists, product managers, and software engineers.

What type of projects will the Machine Learning Engineer work on?

The engineer will contribute to diverse projects, including bid optimization, budget allocation, natural language processing (NLP), and large language models (LLMs).

What qualifications are preferred for the Machine Learning Engineer position?

Preferred qualifications include 2+ years of experience as a Machine Learning Engineer, hands-on experience with AWS, Docker, and Kubernetes, strong Python skills, knowledge of machine learning fundamentals, and experience in debugging complex system issues.

Is experience in AdTech required for this position?

While experience in AdTech is a plus, it is not a strict requirement for the position.

What programming languages and tools will the Machine Learning Engineer be using?

The engineer will primarily use Python for data-intensive tasks, and will also integrate with and query databases such as PostgreSQL and Delta Lake.

What should candidates know about the deployment process?

Candidates should have an understanding of CI/CD pipelines (such as Bitbucket pipelines or GitHub workflows) and familiarity with Terraform is a plus.

How does Radancy Programmatic support team collaboration?

Radancy Programmatic fosters a collaborative team environment where engineers work closely with data scientists and other stakeholders in cross-functional settings.

What kind of solutions will the Machine Learning Engineer be expected to implement regarding model performance?

The engineer will be responsible for hyperparameter optimization across multiple algorithms and implementing long-term solutions to mitigate model concept drift.

What does the working environment at Radancy Programmatic look like?

Employees at Radancy Programmatic work in a supportive and innovative environment, focusing on impactful projects that intersect machine learning with real-world applications.

Is there potential for career growth in this position?

Yes, there are opportunities to grow and expand expertise in cutting-edge technologies like NLP and LLMs while working on significant projects.

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Radancy

Technology
Industry
1001-5000
Employees

Mission & Purpose

Radancy is the leading cloud-based talent acquisition software provider intelligently solving the most critical challenges for enterprises globally and delivering cost-efficient outcomes that strengthen their organizations. The Radancy Talent Acquisition Cloud, powered by rich data and deep industry insights, optimizes the entire candidate journey, enabling enterprises to hire the most qualified talent faster, while reducing costs and driving higher ROI, recruiter efficiency and an improved candidate experience. Headquartered in New York City with a footprint that spans the world, we are one company committed to predicting, defining and creating the future of our industry in partnership with our 1000+ global customers.

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