Senior Data & ML Engineer

Pay rate range - $111/hr. to $115/hr. on W2

Hybrid role

Job Description

The team is looking for a Senior Data & ML Engineer who is curious, driven, and passionate about big data technologies, MLOps, and building a project from scratch.

This role will require participating in full-cycle big data management, processing, infrastructure, and ML system design to build mission-critical, high-volume ML/AI applications to optimize the delivery of relevant and advertising experiences to customers.

As a Senior Engineer, you will operate as a mix of hands-on builder and influencer.

You will work closely with engineers and scientists contributing to the ongoing development and evolution of the underlying machine learning systems and data infrastructures.

Key Job Responsibilities

1. Pairing with product teams, software engineers, data engineers, and scientists to design and develop highly scalable and robust data and ML platforms to serve analytics and production AI/ML models for optimizing advertising reach, frequency, and return on advertising spend.
2. Build scalable and reliable data pipelines that efficiently ingest and process large volumes of data from disparate sources and formats and continuously integrate with internal and external systems.
3. Design and build large-scale data repositories as a knowledge base for GenAI applications.

Basic Qualifications

1. 5+ years of experience as an ML Engineer, Data Engineer, Software Engineer, or in a similar role.
2. Familiarity with the full life cycle of software development, from design and implementation to testing and deployment.
3. Experience with distributed systems and distributed parallel computing frameworks (e.g., Apache Spark, Apache Ray, Dask, etc.)
4. Experience with scaling ML workloads, MLOps, and designing ML systems.
5. Experience with data modeling, data warehousing, and designing ETL workflows.
6. Proficiency in SQL.
7. Proficiency in at least one software programming language of Python, Java, and Scala.
8. Experience working with cloud services (AWS, Azure, GCP, etc.)

Preferred Qualifications

1. Experience working with AWS ecosystem, and development with AWS CDK.
2. Knowledge of Data Privacy, Security, Risk, and Compliance best practices.
3. Experience in machine learning, data mining, information retrieval, statistics or natural language processing.
4. Experience with LLM fine-tuning, developing, evaluating, and deploying LLM for real-world applications.