At a Glance
- Tasks: Lead the development of predictive ML models and deliver actionable insights.
- Company: Join a dynamic team at a cutting-edge tech company.
- Benefits: Enjoy unlimited vacation, hybrid work, and comprehensive health insurance.
- Other info: Collaborative environment with excellent professional development opportunities.
- Why this job: Make a real impact in the exciting field of machine learning.
- Qualifications: Master's or Ph.D. in a related field with proven ML experience.
The predicted salary is between 90900 - 123540 £ per year.
About the Role
We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine‑tuning predictive ML models, with a primary focus on Ad Score and Ad Account Health. You will play a crucial part in delivering actionable insights and solutions to our clients, and your work will be integral to our mission.
Responsibilities
- ML Model Development: Lead the development and refinement of predictive ML models, particularly Ad Score and Ad Account Health.
- Data Analysis: Conduct in-depth data analysis to identify trends, patterns, and insights that inform model development and optimization.
- Feature Engineering: Collaborate with data engineers to create and maintain feature engineering pipelines to support model training.
- Model Evaluation: Implement rigorous evaluation methodologies to assess model performance, making necessary adjustments for continuous improvement.
- Deployment and Integration: Work closely with engineering teams to deploy models and integrate them into our products through APIs.
- Collaboration: Collaborate closely with product managers, full‑stack engineers, and TPMs to ensure seamless integration of data science solutions into our products.
- Research and Innovation: Stay up‑to‑date with the latest developments in the field of data science and machine learning, and explore innovative approaches to problem‑solving.
Requirements
- Master's or Ph.D. in a related field with a strong academic background.
- Proven experience as a Data Scientist with a track record of developing and deploying predictive ML models.
- Expertise in machine learning techniques, including but not limited to regression, classification, clustering, and deep learning.
- Proficiency in data manipulation, feature engineering, and model evaluation.
- Strong programming skills in languages such as Python and experience with libraries like TensorFlow, PyTorch, or scikit‑learn.
- Excellent communication skills and the ability to collaborate effectively within cross‑functional teams.
- A passion for continuous learning and staying updated with the latest trends and technologies in data science.
- Strong problem‑solving abilities and the ability to translate complex data into actionable insights.
Required Knowledge
- Python
- SQL
- Cloud Platforms (GCP, AWS, Azure)
- Data Warehouses (BigQuery, Snowflake, Redshift)
- LLMs / AI APIs
- Git / GitHub
Nice to have
- Data Transformation (dbt)
- Semantic Layers (Cube, Looker, dbt Metrics)
- TypeScript
- Bayesian modeling experience, ideally Marketing Mix Models (PyMC, Stan, or similar), understanding priors, MCMC sampling, posterior diagnostics.
- Causal inference/experimentation – geo experiments (matched markets), A/B testing at scale, familiarity with incrementality measurement.
- Marketing/advertising domain understanding of attribution, media channels (paid social, search, display, video), campaign structures.
- Familiarity with adstock/saturation curves and budget optimization.
Benefits
- Unlimited vacation policy
- Monthly Phone Stipend
- Comprehensive Medical, Dental, and Vision insurance options
- 401(k) plan with matching
- Dog friendly office
- Hybrid work opportunity
- Professional Development Program
Bonus Perk
- Seamless allowance
Total compensation based on education, experience, and skills level: $90,900-$254,100.
Locations:
- New York City: 43‑01 22nd St, Suite 602, Queens, NY 11101, United States
- Bogotá: WeWork Av. Carrera 19 #100‑45 Usaquén, Piso 10, Bogotá, Distrito Capital de Bogotá 110111, Colombia
- Mexico City: Av. Insurgentes Sur 1082, Piso 2, Oficina 2008, Ciudad de México, CDMX 03100, México
Machine Learning Engineer employer: twentysix
Join our dynamic team as a Machine Learning Engineer in New York City, where innovation meets collaboration. We offer a vibrant work culture that encourages professional growth through continuous learning and a comprehensive development programme. Enjoy unique benefits such as an unlimited vacation policy, a dog-friendly office, and a hybrid work opportunity, all while contributing to impactful projects that drive actionable insights for our clients.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Machine Learning Engineers. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those related to predictive models. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and coding challenges. Practice explaining your thought process clearly, as communication is key when collaborating with cross-functional teams.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates like you. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with predictive ML models, data analysis, and any relevant projects that showcase your skills in Python and machine learning libraries.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how your background aligns with our mission at StudySmarter. Don’t forget to mention specific projects or experiences that relate to Ad Score and Ad Account Health.
Showcase Your Problem-Solving Skills:In your application, be sure to highlight your problem-solving abilities. Share examples of how you've tackled complex data challenges in the past, especially those involving model evaluation and feature engineering.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at twentysix
✨Know Your ML Models Inside Out
Make sure you can discuss the predictive ML models you've developed in detail. Be ready to explain your approach to model development, feature engineering, and evaluation methodologies. This shows your expertise and helps you stand out.
✨Showcase Your Data Analysis Skills
Prepare to talk about specific data analysis projects you've worked on. Highlight how you identified trends and insights that informed your model development. Use concrete examples to demonstrate your analytical thinking and problem-solving abilities.
✨Familiarise Yourself with Collaboration Tools
Since collaboration is key in this role, brush up on tools like Git/GitHub and any cloud platforms mentioned in the job description. Being able to discuss how you've used these tools in past projects will show you're ready to integrate seamlessly into their team.
✨Stay Updated on Industry Trends
Research the latest developments in machine learning and data science. Be prepared to discuss recent innovations or techniques you've come across. This not only shows your passion for continuous learning but also your commitment to bringing fresh ideas to the table.
