Production AI Engineer – GenAI & ML Ops

Production AI Engineer – GenAI & ML Ops

Full-Time No working from home possible
Cerberus Capital Management

At a Glance

  • Tasks: Design and deploy production-grade ML systems to enhance investment strategies.
  • Company: Join Cerberus Capital Management, a leader in innovative financial solutions.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Work in a dynamic, agile environment with a focus on innovation.
  • Why this job: Make a real impact by turning research into actionable insights in finance.
  • Qualifications: Experience in AI, ML, and strong collaboration skills are essential.

Cerberus Capital Management seeks an AI engineer to design, implement, and deploy production-grade ML systems across investment desks and portfolio companies. You will build NLP pipelines, integrate models with external services, and drive measurable value through scalable data products.

You'll work in an agile, high-impact environment, collaborating with data scientists, software engineers, and business teams to turn research into deployed solutions that accelerate decision-making.

Production AI Engineer – GenAI & ML Ops employer: Cerberus Capital Management

At Cerberus Capital Management, we pride ourselves on being an exceptional employer that fosters innovation and collaboration in a dynamic environment. As a Production AI Engineer, you'll have the opportunity to work alongside talented professionals, driving impactful projects that enhance decision-making across our investment strategies. Our commitment to employee growth is reflected in our supportive culture and the resources we provide for continuous learning and development.

Cerberus Capital Management

Contact Details:

Cerberus Capital Management Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Production AI Engineer – GenAI & ML Ops

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Cerberus Capital Management!

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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Production AI Engineer – GenAI & ML Ops at Cerberus Capital Management.

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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Cerberus Capital Management.

✨Apply Directly through Our Website

When you find a suitable opening like Production AI Engineer – GenAI & ML Ops at Cerberus Capital Management, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Production AI Engineer – GenAI & ML Ops

Machine Learning
Natural Language Processing (NLP)
Model Integration
Data Product Development
Agile Methodologies
Collaboration Skills
Software Engineering

Some tips for your application 🫑

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Cerberus Capital Management, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Cerberus Capital Management. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Cerberus Capital Management

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Cerberus Capital Management!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.