Senior ML Engineer - Production Pipelines & Systems

Senior ML Engineer - Production Pipelines & Systems

Full-Time No working from home possible
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At a Glance

  • Tasks: Design and build ML pipelines and data workflows for production systems.
  • Company: Join Longshot Systems, a leader in machine learning and data engineering.
  • Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
  • Other info: Collaborative environment with a focus on cutting-edge technology.
  • Why this job: Make an impact by turning innovative models into real-world applications.
  • Qualifications: Experience in ML engineering and proficiency in Python and related tools.

Longshot Systems is hiring Machine Learning Engineers to design, build and productionise ML pipelines and data engineering workflows. You will work across core ML engineering and horse racing teams, turning prototype trading models into production systems using a Python-based stack with tools like PyTorch, Polars and Plotly.

You will design robust data engineering workflows, tooling and scalable software architecture, while collaborating with quantitative researchers to reduce latency.

Senior ML Engineer - Production Pipelines & Systems employer: Longshot Systems

Longshot Systems is an exceptional employer for those passionate about machine learning and sports analytics, offering a dynamic work culture that fosters innovation and collaboration. Employees benefit from opportunities for professional growth through hands-on experience with cutting-edge technologies like Docker, Kubernetes, and cloud platforms, all while contributing to impactful projects in the fast-paced world of sports betting. Located in a vibrant tech hub, the company provides a stimulating environment where creativity and technical expertise thrive.

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Contact Details:

Longshot Systems Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior ML Engineer - Production Pipelines & Systems

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Apply Directly through Our Website

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We think you need these skills to ace Senior ML Engineer - Production Pipelines & Systems

Machine Learning Engineering
Python
PyTorch
Data Engineering
Software Architecture
Collaboration
Quantitative Research

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!

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Craft a Tailored Cover Letter:For a full-time role at Longshot Systems, 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 Longshot Systems. 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 Longshot Systems

Brush Up on Your Statistics

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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 Longshot Systems!

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.