Senior Machine Learning Engineer
YahooAbout the role
A Little About Us:
We are building a team with expertise in machine learning engineering, machine learning modeling and data engineering to enable us to deliver an end-to-end Data Quality & Observability solution. We encourage you to apply if you have expertise in these domains and you are excited to work as a “full-stack” ML engineer.
Yahoo brands comprise some of the premier destinations on the Internet. The Consumer Revenue Data Platform is the central source for trusted, unified consumer revenue data. We are responsible for delivering fast, clean, and relevant data that powers Yahoo’s consumer revenue reporting. Our products empower all consumer business teams to make informed decisions, drive meaningful business value, and manage risk with confidence.
Responsibilities
Understand the technical challenges of a Data Quality product. Think and formulate problems from first principles and map them to one or more Machine Learning paradigms.
Utilizing strong communication skills, iteratively discuss technical ideas cross-functionally.
Define technical requirements, which involves but is not limited to, data collection, evaluation mechanism and production serving strategy.
Based on product requirements, design and implement ML-based solutions and systems that can scale and evolve over time.
Analyze data and identify patterns to inform further development.
Produce technical reports and documentation targeted to both technical and non-technical audiences.
Mentor and train engineers and peers within the team.
Stay updated on industry trends and advancements in technology such as large language and vision models, and generative AI.
Qualifications:
4+ years of track record driving impact in the industry
Master’s degree in Computer Science, Electrical Engineering, Statistics,
Applied Math or related discipline; or, equivalent experience
Expertise in AI, machine learning, deep learning and natural language processing
Required Skills:
MLOps / DevOps
Experience designing, building, and managing scalable infrastructure for training and deploying ML models.
Can build continuous integration and continuous deployment (CI/CD) pipelines to automate the testing, validation, and deployment of ML models.
Strong working knowledge of Google Cloud observability tools to monitor system performance, logs, and metrics.
ML Modeling
Ability to formalize a problem, run reproducible offline experiments and analyze the results.
Experience working with modern ML frameworks (e.g. PyTorch, TensorFlow, Jax).
Strong written communication and data visualization skills (Looker Core, Looker Studio).
Understanding of the difference between “research” code and production code, and when each is appropriate.
Strong knowledge of anomaly detection algorithms.
Data Engineering
Working knowledge of data engineering best practices & data warehousing concepts.
Familiarity with software engineering principles, design patterns, and code quality practices.
Previous working experience in Python and Java, Scala.
Strong Knowledge of GCP
Experience of working with large scale databases like Bigquery
Experience in Data analysis, data investigation and implementing data quality.
Knowledge of workflow/schedulers like Airflow.
#LI-AC1
The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies; exercising sound judgment; working effectively, safely and inclusively with others; exhibiting trustworthiness and meeting expectations; and safeguarding business operations and brand integrity.
At Yahoo, we offer flexible hybrid work options that our employees love! While most roles don’t require regular office attendance, you may occasionally be asked to
Apply for this role
Generate a tailored application kit with a matched cover letter, interview prep, and CV highlights — in under 60 seconds.
Apply Now →Generate Application KitFree account required — sign up in 30s